Academic literature on the topic 'Table annotation'
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Journal articles on the topic "Table annotation"
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CHEN, ENHONG, SHU WANG, and PHILLIP C. Y. SHEU. "A NOVEL APPROACH OF TABLE DETECTION AND ANALYSIS FOR SEMANTIC ANNOTATION." International Journal on Artificial Intelligence Tools 15, no. 03 (June 2006): 465–80. http://dx.doi.org/10.1142/s021821300600276x.
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Semantic web mining is getting more attention in intelligent web applications. Many web sites, especially those dynamically generate HTML pages to display the results of user queries, present information in the form of lists or tables. It is very useful to extract concept instances from these tables for many web applications such as intelligent agent systems for on-line product recommendations. This paper describes a technique for extracting data from tables in two steps, namely table detection and table analysis. The table detection step identifies the existence of a table and extracts its contents, and the table analysis step discovers the semantic meanings embedded in the table and associates them with the concepts described in the domain ontology that are used for semantic annotation on these tables. Our algorithm has been tested based on real-life web documents and the experimental results are encouraging.
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Takeoka, Kunihiro, Masafumi Oyamada, Shinji Nakadai, and Takeshi Okadome. "Meimei: An Efficient Probabilistic Approach for Semantically Annotating Tables." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 281–88. http://dx.doi.org/10.1609/aaai.v33i01.3301281.
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Given a large amount of table data, how can we find the tables that contain the contents we want? A naive search fails when the column names are ambiguous, such as if columns containing stock price information are named “Close” in one table and named “P” in another table.One way of dealing with this problem that has been gaining attention is the semantic annotation of table data columns by using canonical knowledge. While previous studies successfully dealt with this problem for specific types of table data such as web tables, it still remains for various other types of table data: (1) most approaches do not handle table data with numerical values, and (2) their predictive performance is not satisfactory.This paper presents a novel approach for table data annotation that combines a latent probabilistic model with multilabel classifiers. It features three advantages over previous approaches due to using highly predictive multi-label classifiers in the probabilistic computation of semantic annotation. (1) It is more versatile due to using multi-label classifiers in the probabilistic model, which enables various types of data such as numerical values to be supported. (2) It is more accurate due to the multi-label classifiers and probabilistic model working together to improve predictive performance. (3) It is more efficient due to potential functions based on multi-label classifiers reducing the computational cost for annotation.Extensive experiments demonstrated the superiority of the proposed approach over state-of-the-art approaches for semantic annotation of real data (183 human-annotated tables obtained from the UCI Machine Learning Repository).
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Chen, Jiaoyan, Ernesto Jiménez-Ruiz, Ian Horrocks, and Charles Sutton. "ColNet: Embedding the Semantics of Web Tables for Column Type Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 29–36. http://dx.doi.org/10.1609/aaai.v33i01.330129.
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Automatically annotating column types with knowledge base (KB) concepts is a critical task to gain a basic understanding of web tables. Current methods rely on either table metadata like column name or entity correspondences of cells in the KB, and may fail to deal with growing web tables with incomplete meta information. In this paper we propose a neural network based column type annotation framework named ColNet which is able to integrate KB reasoning and lookup with machine learning and can automatically train Convolutional Neural Networks for prediction. The prediction model not only considers the contextual semantics within a cell using word representation, but also embeds the semantics of a column by learning locality features from multiple cells. The method is evaluated with DBPedia and two different web table datasets, T2Dv2 from the general Web and Limaye from Wikipedia pages, and achieves higher performance than the state-of-the-art approaches.
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Huynh, Trung, and Sen Xu. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways." F1000Research 7 (March 29, 2018): 416. http://dx.doi.org/10.12688/f1000research.14012.1.
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We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.
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Huynh, Trung, and Sen Xu. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways." F1000Research 7 (June 28, 2018): 416. http://dx.doi.org/10.12688/f1000research.14012.2.
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We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.
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Huynh, Trung, and Sen Xu. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways." F1000Research 7 (May 9, 2019): 416. http://dx.doi.org/10.12688/f1000research.14012.3.
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We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.
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Thomas, Laurent S. V., Franz Schaefer, and Jochen Gehrig. "Fiji plugins for qualitative image annotations: routine analysis and application to image classification." F1000Research 9 (February 12, 2021): 1248. http://dx.doi.org/10.12688/f1000research.26872.2.
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Quantitative measurements and qualitative description of scientific images are both important to describe the complexity of digital image data. While various software solutions for quantitative measurements in images exist, there is a lack of simple tools for the qualitative description of images in common user-oriented image analysis software. To address this issue, we developed a set of Fiji plugins that facilitate the systematic manual annotation of images or image-regions. From a list of user-defined keywords, these plugins generate an easy-to-use graphical interface with buttons or checkboxes for the assignment of single or multiple pre-defined categories to full images or individual regions of interest. In addition to qualitative annotations, any quantitative measurement from the standard Fiji options can also be automatically reported. Besides the interactive user interface, keyboard shortcuts are available to speed-up the annotation process for larger datasets. The annotations are reported in a Fiji result table that can be exported as a pre-formatted csv file, for further analysis with common spreadsheet software or custom automated pipelines. To illustrate possible use case of the annotations, and facilitate the analysis of the generated annotations, we provide examples of such pipelines, including data-visualization solutions in Fiji and KNIME, as well as a complete workflow for training and application of a deep learning model for image classification in KNIME. Ultimately, the plugins enable standardized routine sample evaluation, classification, or ground-truth category annotation of any digital image data compatible with Fiji.
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Chen, Yongrui, Xinnan Guo, Chaojie Wang, Jian Qiu, Guilin Qi, Meng Wang, and Huiying Li. "Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 5 (May 18, 2021): 3992–4000. http://dx.doi.org/10.1609/aaai.v35i5.16519.
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Single-table text-to-SQL aims to transform a natural language question into a SQL query according to one single table. Recent work has made promising progress on this task by pre-trained language models and a multi-submodule framework. However, zero-shot table, that is, the invisible table in the training set, is currently the most critical bottleneck restricting the application of existing approaches to real-world scenarios. Although some work has utilized auxiliary tasks to help handle zero-shot tables, expensive extra manual annotation limits their practicality. In this paper, we propose a new approach for the zero-shot text-to-SQL task which does not rely on any additional manual annotations. Our approach consists of two parts. First, we propose a new model that leverages the abundant information of table content to help establish the mapping between questions and zero-shot tables. Further, we propose a simple but efficient meta-learning strategy to train our model. The strategy utilizes the two-step gradient update to force the model to learn a generalization ability towards zero-shot tables. We conduct extensive experiments on a public open-domain text-to-SQL dataset WikiSQL and a domain-specific dataset ESQL. Compared to existing approaches using the same pre-trained model, our approach achieves significant improvements on both datasets. Compared to the larger pre-trained model and the tabular-specific pre-trained model, our approach is still competitive. More importantly, on the zero-shot subsets of both the datasets, our approach further increases the improvements.
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Tao, Cui, and David W. Embley. "Automatic hidden-web table interpretation, conceptualization, and semantic annotation." Data & Knowledge Engineering 68, no. 7 (July 2009): 683–703. http://dx.doi.org/10.1016/j.datak.2009.02.010.
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Thomas, Laurent S. V., Franz Schaefer, and Jochen Gehrig. "Fiji plugins for qualitative image annotations: routine analysis and application to image classification." F1000Research 9 (October 15, 2020): 1248. http://dx.doi.org/10.12688/f1000research.26872.1.
Full textAbstract:
Quantitative measurements and qualitative description of scientific images are both important to describe the complexity of digital image data. While various software solutions for quantitative measurements in images exist, there is a lack of simple tools for the qualitative description of images in common user-oriented image analysis software. To address this issue, we developed a set of Fiji plugins that facilitate the systematic manual annotation of images or image-regions. From a list of user-defined keywords, these plugins generate an easy-to-use graphical interface with buttons or checkboxes for the assignment of single or multiple pre-defined categories to full images or individual regions of interest. In addition to qualitative annotations, any quantitative measurement from the standard Fiji options can also be automatically reported. Besides the interactive user interface, keyboard shortcuts are available to speed-up the annotation process for larger datasets. The annotations are reported in a Fiji result table that can be exported as a pre-formatted csv file, for further analysis with common spreadsheet software or custom automated pipelines. To facilitate and spread the usage of analysis tools, we provide examples of such pipelines, including a complete workflow for training and application of a deep learning model for image classification in KNIME. Ultimately, the plugins enable standardized routine sample evaluation, classification, or ground-truth category annotation of any digital image data compatible with Fiji.
Dissertations / Theses on the topic "Table annotation"
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CUTRONA, VINCENZO. "Semantic Table Annotation for Large-Scale Data Enrichment." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/317044.
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I dati rappresentano uno dei principali asset che creano valore.
L'analisi dei dati è diventata una componente cruciale negli studi scientifici e nelle decisioni aziendali negli ultimi anni e ha portato i ricercatori a definire nuove metodologie per rappresentare, gestire e analizzare i dati. Contemporaneamente, la crescita della potenza di calcolo ha permesso l'analisi di enormi quantità di dati, permettendo alle persone di estrarre informazioni utili dai dati raccolti.
L'analisi predittiva gioca un ruolo cruciale in molte applicazioni poiché fornisce più conoscenza per supportare le decisioni aziendali. Tra le tecniche statistiche disponibili per supportare l'analitica predittiva, l'apprendimento automatico è una tecnica capace di risolvere molte classi diverse di problemi, e che ha beneficiato maggiormente della crescita della potenza di calcolo.
Infatti, negli ultimi anni, sono stati proposti modelli di apprendimento automatico più complessi e accurati, che richiedono una quantità crescente di dati attuali e storici per funzionare al meglio.
La richiesta di una quantità così massiccia di dati per addestrare i modelli di apprendimento automatico rappresenta un ostacolo iniziale per i data scientist, perché le informazioni necessarie sono di solito sparse in diversi set di dati che devono essere integrati manualmente. Di conseguenza, l'arricchimento dei dati è diventato un compito critico nel processo di preparazione dei dati, e al giorno d'oggi, la maggior parte dei progetti prevedere un processo di preparazione dei dati costoso in termini di tempo, volto ad arricchire un set di dati principali con informazioni aggiuntive da varie fonti esterne per migliorare la solidità dei modelli addestrati risultanti. Come facilitare la progettazione del processo di arricchimento per gli scienziati dei dati è una sfida, così come sostenere il processo di arricchimento su larga scala. Nonostante la crescente importanza dell'attività di arricchimento, essa è ancora supportata solo in misura limitata dalle soluzioni esistenti, delegando la maggior parte dello sforzo al data scientist, che è incaricato sia di rilevare i set di dati che contengono le informazioni necessarie, sia di integrarli.
In questa tesi, introduciamo una metodologia per supportare l'attività di arricchimento dei dati, che si concentra sullo sfruttamento della semantica come fattore chiave, fornendo agli utenti uno strumento semantico per progettare il processo di arricchimento, insieme a una piattaforma per eseguire il processo su larga scala. Illustriamo come l'arricchimento dei dati può essere affrontato tramite trasformazioni di dati tabellari, sfruttando metodi di interpretazione semantica delle tabelle, e discutiamo le tecniche di implementazione per supportare l'esecuzione del processo risultante su grandi set di dati. Dimostriamo sperimentalmente la scalabilità e l'efficienza della soluzione proposta impiegandola in uno scenario del mondo reale.
Infine, introduciamo un nuovo set di dati di riferimento per valutare le prestazioni e la scalabilità degli algoritmi di annotazione semantica delle tabelle, e proponiamo un nuovo approccio efficiente per migliorare le prestazioni di tali algoritmi.Data are the new oil, and they represent one of the main value-creating assets. Data analytics has become a crucial component in scientific studies and business decisions in the last years and has brought researchers to define novel methodologies to represent, manage, and analyze data. Simultaneously, the growth of computing power enabled the analysis of huge amounts of data, allowing people to extract useful information from collected data. Predictive analytics plays a crucial role in many applications since it provides more knowledge to support business decisions. Among the statistical techniques available to support predictive analytics, machine learning is the technique that features capabilities to solve many different classes of problems, and that has benefited the most from computing power growth. In the last years, more complex and accurate machine learning models have been proposed, requiring an increasing amount of current and historical data to perform the best. The demand for such a massive amount of data to train machine learning models represents an initial hurdle for data scientists because the information needed is usually scattered in different data sets that have to be manually integrated. As a consequence, data enrichment has become a critical task in the data preparation process, and nowadays, most of all the data science projects involve a time-costly data preparation process aimed at enriching a core data set with additional information from various external sources to improve the sturdiness of resulting trained models. How to ease the design of the enrichment process for data scientists is defying and supporting the enrichment process at a large scale. Despite the growing importance of the enrichment task, it is still supported only to a limited extent by existing solutions, delegating most of the effort to the data scientist, who is in charge of both detecting the data sets that contain the needed information, and integrate them. In this thesis, we introduce a methodology to support the data enrichment task, which focuses on harnessing the semantics as the key factor by providing users with a semantics-aided tool to design the enrichment process, along with a platform to execute the process at a business scale. We illustrate how the data enrichment can be addressed via tabular data transformations exploiting semantic table interpretation methods, discussing implementation techniques to support the enactment of the resulting process on large data sets. We experimentally demonstrate the scalability and run-time efficiency of the proposed solution by employing it in a real-world scenario. Finally, we introduce a new benchmark dataset to evaluate the performance and the scalability of existing semantic table annotation algorithms, and we propose an efficient novel approach to improve the performance of such algorithms.
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Tao, Cui. "Ontology Generation, Information Harvesting and Semantic Annotation for Machine-Generated Web Pages." BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1646.
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The current World Wide Web is a web of pages. Users have to guess possible keywords that might lead through search engines to the pages that contain information of interest and browse hundreds or even thousands of the returned pages in order to obtain what they want. This frustrating problem motivates an approach to turn the web of pages into a web of knowledge, so that web users can query the information of interest directly. This dissertation provides a step in this direction and a way to partially overcome the challenges. Specifically, this dissertation shows how to turn machine-generated web pages like those on the hidden web into semantic web pages for the web of knowledge. We design and develop three systems to address the challenge of turning the web pages into web-of-knowledge pages: TISP (Table Interpretation for Sibling Pages), TISP++, and FOCIH (Form-based Ontology Creation and Information Harvesting). TISP can automatically interpret hidden-web tables. Given interpreted tables, TISP++ can generate ontologies and semantically annotate the information present in the interpreted tables automatically. This way, we can offer a way to make the hidden information publicly accessible. We also provide users with a way where they can generate personalized ontologies. FOCIH provides users with an interface with which they can provide their own view by creating a form that specifies the information they want. Based on the form, FOCIH can generate user-specific ontologies, and based on patterns in machine-generated pages, FOCIH can harvest information and annotate these pages with respect to the generated ontology. Users can directly query on the annotated information. With these contributions, this dissertation serves as a foundational pillar for turning the current web of pages into a web of knowledge.
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Milosevic, Nikola. "A multi-layered approach to information extraction from tables in biomedical documents." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/a-multilayered-approach-to-information-extraction-from-tables-in-biomedical-documents(c2edce9c-ae7f-48fa-81c2-14d4bb87423e).html.
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The quantity of literature in the biomedical domain is growing exponentially. It is becoming impossible for researchers to cope with this ever-increasing amount of information. Text mining provides methods that can improve access to information of interest through information retrieval, information extraction and question answering. However, most of these systems focus on information presented in main body of text while ignoring other parts of the document such as tables and figures. Tables present a potentially important component of research presentation, as authors often include more detailed information in tables than in textual sections of a document. Tables allow presentation of large amounts of information in relatively limited space, due to their structural flexibility and ability to present multi-dimensional information. Table processing encapsulates specific challenges that table mining systems need to take into account. Challenges include a variety of visual and semantic structures in tables, variety of information presentation formats, and dense content in table cells. The work presented in this thesis examines a multi-layered approach to information extraction from tables in biomedical documents. In this thesis we propose a representation model of tables and a method for table structure disentangling and information extraction. The model describes table structures and how they are read. We propose a method for information extraction that consists of: (1) table detection, (2) functional analysis, (3) structural analysis, (4) semantic tagging, (5) pragmatic analysis, (6) cell selection and (7) syntactic processing and extraction. In order to validate our approach, show its potential and identify remaining challenges, we applied our methodology to two case studies. The aim of the first case study was to extract baseline characteristics of clinical trials (number of patients, age, gender distribution, etc.) from tables. The second case study explored how the methodology can be applied to relationship extraction, examining extraction of drug-drug interactions. Our method performed functional analysis with a precision score of 0.9425, recall score of 0.9428 and F1-score of 0.9426. Relationships between cells were recognized with a precision of 0.9238, recall of 0.9744 and F1-score of 0.9484. The information extraction methodology performance is the state-of-the-art in table information extraction recording an F1-score range of 0.82-0.93 for demographic data, adverse event and drug-drug interaction extraction, depending on the complexity of the task and available semantic resources. Presented methodology demonstrated that information can be efficiently extracted from tables in biomedical literature. Information extraction from tables can be important for enhancing data curation, information retrieval, question answering and decision support systems with additional information from tables that cannot be found in the other parts of the document.
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Christopher, Mark Allen. "Truthmarker: a tablet-based approach for rapid image annotation." Thesis, University of Iowa, 2011. https://ir.uiowa.edu/etd/2686.
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The development of automated techniques for the analysis of image data is an important and active area of research. To make progress, this research requires annotations of image data to build and validate models used for analysis. Given this requirement, the development of software tools that streamline the collection of annotations would be of great benefit to image analysis researchers. Such tools should meet the following requirements: rapid generation of annotations for large data sets, annotation and data management that is straightforward for users, flexibility for application to many diverse image datasets, configurability to allow the collection of annotations to be tuned for a specific research goal, and generation of annotation data in a standardized format so that it can be easily parsed and analyzed. Truthmarker was designed as a tablet computer based image annotation tool to meet these requirements. Researchers can configure Truthmarker to fit the needs of a particular study by specifying an annotation model that fine tunes the user interface and resulting data to fit the annotation task. The quality of annotations generated using Truthmarker was evaluated by recruiting medical experts to annotate ophthalmic images for severity of diabetic retinopathy, a leading cause of blindness. These annotations were compared to annotations of the same images assigned using standard desktop computer based tools. The results, as measured by κ statistics and accuracy, indicate that Truthmarker annotations were of equivalent quality compared to those that were created using desktop-based tools.
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Palladino, Chiara. "Round table report." Universitätsbibliothek Leipzig, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-221622.
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Palladino, Chiara. "Round table report: Epigraphy Edit-a-thon: editing chronological and geographic data in ancient inscriptions: April 20-22, 2016." Epigraphy Edit-a-thon : editing chronological and geographic data in ancient inscriptions ; April 20-22, 2016 / edited by Monica Berti. Leipzig, 2016. Beitrag 15, 2016. https://ul.qucosa.de/id/qucosa%3A15477.
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Doukhan, David. "Synthèse de parole expressive au delà du niveau de la phrase : le cas du conte pour enfant : conception et analyse de corpus de contes pour la synthèse de parole expressive." Thesis, Paris 11, 2013. http://www.theses.fr/2013PA112165/document.
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L'objectif de la thèse est de proposer des méthodes permettant d'améliorer l'expressivité des systèmes de synthèse de la parole. Une des propositions centrales de ce travail est de définir, utiliser et mesurer l'impact de structures linguistiques opérant au delà du niveau de la phrase, par opposition aux approches opérant sur des phrases isolées de leur contexte. Le cadre de l'étude est restreint au cas de la lecture de contes pour enfants. Les contes ont la particularité d'avoir été l'objet d'un certain nombre d'études visant à en dégager une structure narrative et de faire intervenir une certain nombre de stéréotypes de personnages (héros, méchant, fée) dont le discours est souvent rapporté. Ces caractéristiques particulières sont exploitées pour modéliser les propriétés prosodiques des contes au delà du niveau de la phrase. La transmission orale des contes a souvent été associée à une pratique musicale (chants, instruments) et leur lecture reste associée à des propriétés mélodiques très riches, dont la reproduction reste un défi pour les synthétiseurs de parole modernes. Pour répondre à ces problématiques, un premier corpus de contes écrits est collecté et annoté avec des informations relatives à la structure narrative des contes, l'identification et l'attribution des citations directes, le référencement des mentions des personnages ainsi que des entités nommées et des énumérations étendues. Le corpus analysé est décrit en terme de couverture et d'accord inter-annotateurs. Il est utilisé pour modéliser des systèmes de segmentation des contes en épisode, de détection des citations directes, des actes de dialogue et des modes de communication. Un deuxième corpus de contes lus par un locuteur professionnel est présenté. La parole est alignée avec les transcriptions lexicale et phonétique, les annotations du corpus texte et des méta-informations décrivant les caractéristiques des personnages intervenant dans le conte. Les relations entre les annotations linguistiques et les propriétés prosodiques observées dans le corpus de parole sont décrites et modélisées. Finalement, un prototype de contrôle des paramètres expressifs du synthétiseur par sélection d'unités Acapela est réalisé. Le prototype génère des instructions prosodiques opérant au delà du niveau de la phrase, notamment en utilisant les informations liées à la structure du conte et à la distinction entre discours direct et discours rapporté. La validation du prototype de contrôle est réalisée dans le cadre d'une expérience perceptive, qui montre une amélioration significative de la qualité de la synthèseThe aim of this thesis is to propose ways to improve the expressiveness of speech synthesis systems. One of the central propositions of this work is to define, use and measure the impact of linguistic structures operating beyond the sentence level, as opposed to approaches operating on sentences out of their context. The scope of the study is restricted to the case of storytelling for children. The stories have the distinction of having been the subject of a number of studies in order to highlight a narrative structure and involve a number of stereotypical characters (hero, villain, fairy) whose speech is often reported. These special features are used to model the prosodic properties tales beyond the sentence level. The oral transmission of tales was often associated with musical practice (vocals, instruments) and their reading is associated with rich melodic properties including reproduction remains a challenge for modern speech synthesizers. To address these issues, a first corpus of written tales is collected and annotated with information about the narrative structure of stories, identification and allocation of direct quotations, referencing references to characters as well as named entities and enumerations areas. The corpus analyzed is described in terms of coverage and inter-annotator agreement. It is used to model systems segmentation tales episode, detection of direct quotes, dialogue acts and modes of communication. A second corpus of stories read by a professional speaker is presented. The word is aligned with the lexical and phonetic transcriptions, annotations of the corpus text and meta-information describing the characteristics of the characters involved in the story. The relationship between linguistic annotations and prosodic properties observed in the speech corpus are described and modeled. Finally, a prototype control expressive synthesizer parameters by Acapela unit selection is made. The prototype generates prosodic operating instructions beyond the sentence level, including using the information related to the structure of the story and the distinction between direct speech and reported speech. Prototype validation control is performed through a perceptual experience, which shows a significant improvement in the quality of the synthesis
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Singh, Varinder. "GestAnnot: A Paper Annotation Tool for Tablet." 2013. http://hdl.handle.net/10222/42725.
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Active Reading is an important part of a knowledge worker’s activities; it involves highlighting, writing notes, marking with symbols, etc., on a document. Many Active Reading applications have been designed in seeking to replicate the affordances of paper through digital-ink-based annotation tools. However, these applications require users to perform numerous steps to use various types of annotation tools, which impose an unnecessary cognitive load, distracting them from their reading tasks. In this thesis, we introduce GestAnnot, an Active Reading application for tablet computers that takes a fundamentally different approach of incorporating multi-touch gesture techniques for creating and manipulating annotations on an e-document, thus offering a flexible and easy- to-use annotation solution. Based on the literature review, we designed and developed GestAnnot and then performed lab and field evaluations of the software. In lab evaluation, GestAnnot performed better than one of the best existing annotation application in many aspects, including number of steps. The design was then refined based on the feedback received. The field evaluation of the improved design helped us to understand the performance of the application in the real world. We proposed a set of design guidelines through the feedback received from both evaluations, which any future Active Reading application could benefit from.
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Huang, Albert. "Ad-hoc Collaborative Document Annotation on a Tablet PC." 2003. http://hdl.handle.net/1721.1/3847.
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The use of technology as an effective educational tool has been an elusive goal in the past. Specifically, previous attempts at using small personal computers in the classroom to aid students as collaborative and note-taking tools have been met with lukewarm responses. Many of these past attempts were hampered by inferior hardware and the lack of an efficient and user-friendly interface. With the recent introduction of Tablet PC products on the market, however, the limitations imposed on software developers for mobile computing systems have been dramatically lowered. We present a collaborative annotation system that allows students equipped with tablet computers to work cooperatively in either an ad-hoc or a structured wireless classroom setting.Singapore-MIT Alliance (SMA)
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Neale, SJ. "A Hands-on, mobile approach to collaborative exploration and discussion of virtual museum artefacts." Thesis, 2014. https://eprints.utas.edu.au/22755/1/whole_Neale_thesis.pdf.
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For the visitors who frequent them, museums are a gateway and a window to culture, a place where “children and adults can leisurely browse” exhibitions and displays to discover endless aspects of history and science, and “seek and find meaning and connection” (Falk and Dierking, 2000). The public perception of museums has long been one of “tried--‐and--‐true sources of understandable information”, and as places where “reliable, authentic, and comprehensible presentations of art, history, natural history, and science objects and ideas” can be digested (Falk and Dierking, 2000). The museum is a place where people can connect with the facts, ideas, cultures, and scientific theories that underpin human and natural history, as well as the modern world that history has shaped. Besides simply being information sources, for many visitors museums are also associated with the storage and maintenance of physical records and objects. Museums are seen as places where “treasures, both physical and intellectual, are preserved and displayed” for public consumption (Falk and Dierking, 1992), and because of this the strength and importance of museums in society is not just down to the knowledge, but also the collections that they possess (Falk and Dierking, 2000). The focus of museums has started to change as the information age continues to shape the way people communicate with each other, share information, and learn from and about the world in which they live. Museums have had, and continue to, evolve in order to support the changing characteristics and demands of their audience, an evolution which necessitates “a more sophisticated understanding of the complex relationships between culture, communication, learning and identity” (Hooper--‐Greenhill, 2007). In order for museums to remain diversity”, and when explored through touch can act as storytelling tools that hold secrets and reveal answers for the inquisitive learner (Chatterjee, 2010). Much of the importance that artefacts are able to transmit is due to the ability of a real, physical thing to “[connect] people across time and culture that they have no tangible contact with otherwise”, which gives learners handling, viewing or experiencing an object a “strong personal connection to the past and to the makers and users of the object” (Boyes and Cousens, 2012) (Mastoris, n.d.). This connection that artefacts facilitate between their users or creators and the museum visitors exploring them can evoke deep emotional responses and involvement (Chatterjee, 2007) (Boyes and Cousens, 2012), and it is important that museum professionals realise the power that this “almost magical” experience of touching or handling artefacts can produce (Pye, 2007). This connection between handler and artefact is potentially an important learning tool in museums. Here, artefacts are “conveyors of knowledge and understanding that inspire discussion, group work and lateral thinking” (Boyes and Cousens, 2012) (Chatterjee, 2010) – exactly the kind of collaborative activities that museums are encouraging their visitors to involve themselves in as part of a group or community of learners. The ‘conveying of knowledge’ occurs when artefacts are used as “prompt[s]” to memories (whether that be of someone, something or somewhere) and as “a point of departure for learning and creativity” (Mastoris, n.d.). For example, handling “an unfamiliar object” encourages museum visitors to imagine “what it would be like to use it”, which in turn “may prompt [a] deeper understanding” of what life, activities, or processes would have been like for the makers, users, or discoverers of the artefact (Trewinnard--‐Boyle and Tabassi, 2007). Existing research has suggested that ‘object--‐based learning’ plays an important role in active, experiential learning strategies (Chatterjee, 2010). Physical objects are 3D experiences, “more tactile than a picture or a recording” and often involving moving parts (Mastoris, n.d.), and being able to turn them over and look at them from all sides gives handlers and viewers an increased awareness of physical characteristics such as colour, weight, texture and scale (Boyes and Cousens, 2012). Besides the experiential benefits of tactile exploration that help handlers to understand the physical properties of objects, museum artefacts in particular can also act as “a ’focal point’ that can enhance and disseminate subject knowledge”, revealing their history and cultural importance by inspiring the handler and inducing their practical and observational skills (Chatterjee, 2007) (Chatterjee, 2010). This ‘conveying of knowledge’ that artefacts facilitate, as described in the previous subsection, is especially prominent in collaborative scenarios, where the artefact acts as a focal point and a spatial reference for directing a discussion between a group of handlers as they collaboratively explore and make sense of both its physical properties and its historical and cultural significance. However, despite museum collections being full of exciting and valuable artefacts, most of the artefacts in a particular collection will be “inaccessible to the normal visitor”, with “relatively few” of the objects that make up a particular collection actually being on display at any given moment (Pye, 2007). In recent years, with the advent of advanced digital imaging techniques and web technologies, museums have begun displaying artefacts from their collections online, but despite being available to anybody with an internet connection, artefacts displayed using digital imagery tend to lack the participatory, tactile qualities of “flesh and blood” objects (Pye, 2007). There are also many scenarios in which, even when an artefact is on display, it is still inaccessible – an artefact might be positioned behind barriers, displayed in a glass case, or displayed in low light levels (Pye, 2007). For collaborative discussions in particular, physical access to artefacts is also affected by location, with two or more potential collaborators often not being in the same location as the artefact, as each other, or both. This can be problematic in scenarios such as discussions of artefacts amongst online communities (digital museum visitors), between curators in different museums around the world, or during long distance lectures, presentations or discussions delivered online. Staff from the Queen Victoria Museum & Art Gallery (QVMAG) in Launceston, Tasmania described to us an example scenario of museum curators considering the purchase of an artefact from another museum situated overseas. With time, money, and potentially the museum’s reputation at stake, it is hugely advantageous for curators to be able to understand the physical properties of artefacts before committing to a decision, even if they are not able to handle them in person. Currently, this is difficult to facilitate using remote--‐collaborative methods such as video conferencing or the sharing of still digital images. There is a huge benefit to be gained from manual interaction with museum artefacts. Being able to explore an artefact with the hands gives visitors an understanding of its physical properties and nuances, and allows it to become a focal point for making sense of its historical and cultural associations through active, experiential exploration, particularly as part of a collaborative discussion. But with access to museum artefacts often limited as a result of artefacts and those who wish to explore them being in different locations, this kind of exploration from all sides and angles is not always possible and the vital spatial referencing and physical understanding that handling artefacts provides is lost. This seems like something of a missed opportunity for participatory, collaborative museum learning activities. Providing experiences that support and encourage participatory activities for communities of museum learners is a key objective for museums, and the reason it should be so is exemplified by the way in which people visit museums. The Australian Museum has estimated that 45--‐55% of their visitors arrive in the form of family groups, 15% as pairs and partners, and another 15% as organised school or educational groups – that’s up to 85% of the visitors to the museum arriving as part of a group, with as little as 15% visiting alone (Black, 2005). As well as making practical sense to target groups of visitors in so much as that such a large majority of people visit museums together, engaging visitors as partners in collaborative activity also has learning benefits, with adults in particular having been observed to have their “need to know” satisfied by collaborative activities that “[appeal] to their self--‐concept as independent learners” (Knowles et al., 2005). Museum visitors not only feel that they are learning something independently, but also feel like they are contributing to the learning outcomes of others, which can be a very engaging sensation. As well as servicing communities of learners, collaboration is also important in that many museum collections “may continue to be of ‘deep significance’ to the specific communities from which artefacts come” (Pye, 2007). Communities descended from the colonial or indigenous groups that artefacts come from “are increasingly eager to gain access to their ancestral objects”, the handling of which provides them with “opportunities for reminiscence and sharing of information”, “enables communities to study techniques and materials” and gives community members, young and old, the chance to “regain [and revisit] traditional craft skills and cultural practices” (Pye, 2007).
Books on the topic "Table annotation"
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Group, West, ed. ALR index, covering ALR 2d, ALR 3d, ALR 4th, ALR 5th ... ALR Fed ...: Also containing table of laws, rules, and regulations, annotation history table. [St. Paul, Minn.]: West Group, 1999.
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Company, Lawyers Co-operative Publishing, and Bancroft-Whitney Company, eds. Index to annotations: Covering ALR 2d, ALR 3d, ALR 4th, vols. 1-49, ALR fed, vols. 1-79, Led 2d, vols. 1-81 : also containing table of laws, rules, and regulations, annotation history table. Rochester, N.Y: Lawyers Co-operative Pub. Co., 1986.
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Group, West. ALR index: Covering ALR 2d, ALR 3d, ALR 4th, ALR 5th, vols. 1-88, ALR fed, vols. 1-170 : also containing annotation history table. [St. Paul, Minn.]: West Group, 1992.
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Group, West, ed. ALR index: Covering ALR 2d, ALR 3d, ALR 4th, ALR 5th, vols. 1-69, ALR Fed, vols. 1-155 : also containing table of laws, rules, and regulations, annotation history table.
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(Firm), West. ALR index: Covering ALR, ALR 2d, ALR 3d, ALR 4th, ALR 5th, ALR 6th, vols. 1-35, ALR federal, ALR federal 2d, vols. 1-30 : also containing annotation history table. Egan, MN: Thomson/West, 2008.
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juridique, Société québécoise d'information. Table de la jurisprudence citée, 1980-1987. [Montréal]: La Société, 1989.
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Fishman, Joel. Pennsylvania county reports and district & county reports: Parallel citation tables. Pittsburgh: Allegheny County Law Library, 1985.
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Publishing, Academy. Comparative table of citations, 1965 to 2009: Singapore law reports (Reissue). Singapore: Academy Publishing, 2010.
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Police, Maine State. Maine statutory citation table for SBI reporting. [Augusta, Me: Maine State Police], 2004.
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Rao, A. V. Raman. Supreme Court index to case law, 1950-1991: With statutory subject index & comparative tables. Delhi: Allied Book Co., 1992.
Find full textBook chapters on the topic "Table annotation"
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Moon, Keon-Woong. "Add a Table Annotation." In Use R!, 241–46. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-53019-2_24.
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Ciavotta, Michele, Vincenzo Cutrona, Flavio De Paoli, Nikolay Nikolov, Matteo Palmonari, and Dumitru Roman. "Supporting Semantic Data Enrichment at Scale." In Technologies and Applications for Big Data Value, 19–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-78307-5_2.
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AbstractData enrichment is a critical task in the data preparation process in which a dataset is extended with additional information from various sources to perform analyses or add meaningful context. Facilitating the enrichment process design for data workers and supporting its execution on large datasets are only supported to a limited extent by existing solutions. Harnessing semantics at scale can be a crucial factor in effectively addressing this challenge. This chapter presents a comprehensive approach covering both design- and run-time aspects of tabular data enrichment and discusses our experience in making this process scalable. We illustrate how data enrichment steps of a Big Data pipeline can be implemented via tabular transformations exploiting semantic table annotation methods and discuss techniques devised to support the enactment of the resulting process on large tabular datasets. Furthermore, we present results from experimental evaluations in which we tested the scalability and run-time efficiency of the proposed cloud-based approach, enriching massive datasets with promising performance.
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Hignette, Gaëlle, Patrice Buche, Juliette Dibie-Barthélemy, and Ollivier Haemmerlé. "An Ontology-Driven Annotation of Data Tables." In Web Information Systems Engineering – WISE 2007 Workshops, 29–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-77010-7_4.
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van Assem, Mark, Hajo Rijgersberg, Mari Wigham, and Jan Top. "Converting and Annotating Quantitative Data Tables." In Lecture Notes in Computer Science, 16–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17746-0_2.
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Hignette, Gaëlle, Patrice Buche, Juliette Dibie-Barthélemy, and Ollivier Haemmerlé. "Semantic Annotation of Data Tables Using a Domain Ontology." In Discovery Science, 253–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75488-6_25.
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Hignette, Gaëlle, Patrice Buche, Juliette Dibie-Barthélemy, and Ollivier Haemmerlé. "Fuzzy Annotation of Web Data Tables Driven by a Domain Ontology." In Lecture Notes in Computer Science, 638–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02121-3_47.
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Lee, Jang Ho. "Design of Tablet-Based Live Mobile Learning System Supporting Improved Annotation." In Advances in Computer Science and Ubiquitous Computing, 221–26. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9343-7_30.
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Thompson, Cristiane C., Livia Vidal, Vinicius Salazar, Jean Swings, and Fabiano L. Thompson. "Microbial Genomic Taxonomy." In Trends in the systematics of bacteria and fungi, 168–78. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789244984.0168.
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Abstract This book chapter argues for an open-access catalogue of taxonomic descriptions with prototypes; diagnostic tables; and links to culture collections, to genome and gene sequences, and to other phenotypic and ecological databases. Ideally, the open access taxonomy will be based solely on genome sequences that allow both the phylogenetic allocation of new strains and species in the taxonomic space and the phenotypic/metabolic characterization in open online databases. Careful and thorough annotation of the genome sequences for function and chemotaxonomic data will be required. An alternative Code will be required for the naming strategy of genomes. Current microbial taxonomy is not able to keep up with the pace of development in microbial ecology. Innovative ways of developing microbial taxonomy are, therefore, needed urgently. This novel approach can, for the first time, allow microbial species descriptions using genomes based on ecological and evolutionary theory. One challenge ahead is to leverage the use of genome sequences to obtain insights on the (in silico) phenotypes and ecology of novel taxa.
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Cabral, Diogo, and Nuno Correia. "Pen-Based Video Annotations: A Proposal and a Prototype for Tablet PCs." In Human-Computer Interaction – INTERACT 2009, 17–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03658-3_5.
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Touhami, Rim, Patrice Buche, Juliette Dibie-Barthélemy, and Liliana Ibănescu. "An Ontological and Terminological Resource for n-ary Relation Annotation in Web Data Tables." In On the Move to Meaningful Internet Systems: OTM 2011, 662–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25106-1_19.
Full textConference papers on the topic "Table annotation"
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Olegovich Dorodnykh, Nikita, Alexey Olegovich Shigarov, and Aleksandr Yurevich Yurin. "Using the Semantic Annotation of Web Table Data for Knowledge Base Construction." In AICCC '21: 2021 4th Artificial Intelligence and Cloud Computing Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3508259.3508277.
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Chen, Jiaoyan, Ernesto Jimenez-Ruiz, Ian Horrocks, and Charles Sutton. "Learning Semantic Annotations for Tabular Data." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/289.
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The usefulness of tabular data such as web tables critically depends on understanding their semantics. This study focuses on column type prediction for tables without any meta data. Unlike traditional lexical matching-based methods, we propose a deep prediction model that can fully exploit a table’s contextual semantics, including table locality features learned by a Hybrid NeuralNetwork (HNN), and inter-column semantics features learned by a knowledge base (KB) lookup and query answering algorithm. It exhibits good performance not only on individual table sets, but also when transferring from one table set to another.
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Cao, Huanhuan, Lili Liu, Bocheng Lin, and Lishan Zhang. "A Computer Supported Collaborative Annotation System." In 2021 IEEE International Conference on Engineering, Technology & Education (TALE). IEEE, 2021. http://dx.doi.org/10.1109/tale52509.2021.9678517.
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Quercini, Gianluca, and Chantal Reynaud. "Entity discovery and annotation in tables." In the 16th International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2452376.2452457.
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Hudelist, Marco A., Sabrina Kletz, and Klaus Schoeffmann. "A Tablet Annotation Tool for Endoscopic Videos." In MM '16: ACM Multimedia Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2964284.2973822.
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Reinoso, Martin, Thuong N. Hoang, Frank Vetere, and Egemen Tanin. "Annotating Animated AR Objects for Co-located Learning." In 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE). IEEE, 2018. http://dx.doi.org/10.1109/tale.2018.8615452.
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Silva, João, Diogo Cabral, Carla Fernandes, and Nuno Correia. "Real-time annotation of video objects on tablet computers." In the 11th International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2406367.2406391.
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Cabral, Diogo, João M. F. Silva, Carla Fernandes, and Nuno Correia. "Annotating Live Video with Tablet Computers." In AVI '16: International Working Conference on Advanced Visual Interfaces. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2909132.2926069.
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Yoshimori, Kanako. "Annotation and Practice of Reading: The Tale of Genji and Kakaisho." In The Asian Conference on Cultural Studies 2020. The International Academic Forum(IAFOR), 2020. http://dx.doi.org/10.22492/issn.2187-4751.2020.6.
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Eslahi, Yasamin, Akansha Bhardwaj, Paolo Rosso, Kurt Stockinger, and Philippe Cudre-Mauroux. "Annotating Web Tables through Knowledge Bases: A Context-Based Approach." In 2020 7th Swiss Conference on Data Science (SDS). IEEE, 2020. http://dx.doi.org/10.1109/sds49233.2020.00013.
Full textReports on the topic "Table annotation"
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Blumwald, Eduardo, and Avi Sadka. Sugar and Acid Homeostasis in Citrus Fruit. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7697109.bard.
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Citrus fruit quality standards have been determined empirically, depending on species and on the particular growing regions. In general, the TSS (total soluble solids) to total acidity (TA) ratio determines whether citrus fruit can be marketed. Soluble sugars account for most of the TSS during harvest while TA is determined almost solely by the citric acid content, which reaches levels of 1-5% by weight in many cultivated varieties. Acid and sugar homeostasis in the fruit is critical for the management of existing cultivars, the development of new cultivars, the improvement of pre- and post-harvest strategies and the control of fruit quality and disorders. The current proposal (a continuation of a previous proposal) aimed at: (1) completing the citrus fruit proteome and metabolome, and establish a citrus fruit functional database, (2) further characterization of the control of fruit acidity by studying the regulation of key steps affecting citrate metabolism, and determine the fate of citrate during acid decline stage, and (3) Studying acid and sugar homeostasis in citrus fruits by characterizing transport mechanisms across membranes. These aims were completed as the following: (1) Our initial efforts were aimed at the characterization and identification of citric acid transporters in citrus juice cells. The identification of citrate transporters at the vacuole of the citrus juice cell indicated that the steady-state citrate cytosolic concentration and the action of the cytosolic aconitase were key elements in establishing the pH homeostat in the cell that regulates the metabolic shift towards carbon usage in the fruit during the later stages of fruit development. We focused on the action of aconitase, the enzyme mediating the metabolic use of citric acid in the cells, and identified processes that control carbon fluxes in developing citrus fruits that control the fruit acid load; (2) The regulation of aconitase, catalyzing a key step in citrate metabolism, was further characterized by using two inhibitors, citramalte and oxalomalte. These compounds significantly increased citrate content and reduced the enzyme’s activity. Metabolite profiling and changes of amino-acid metabolizing enzymes in oxalomalate- treated cells suggested that the increase in citrate, caused by aconitase inhibition, induces amino acid synthesis and the GABA shunt, in accordance with the suggested fate of citrate during the acid decline stage in citrus fruit. (3) We have placed a considerable amount of time on the development of a citrus fruit proteome that will serve to identify all of the proteins in the juice cells and will also serve as an aid to the genomics efforts of the citrus research community (validating the annotation of the fruit genes and the different ESTs). Initially, we identified more than 2,500 specific fruit proteins and were able to assign a function to more than 2,100 proteins (Katz et al., 2007). We have now developed a novel Differential Quantitative LC-MS/MS Proteomics Methodology for the identification and quantitation of key biochemical pathways in fruits (Katz et al., 2010) and applied this methodology to identify determinants of key traits for fruit quality (Katz et al., 2011). We built “biosynthesis maps” that will aid in defining key pathways associated with the development of key fruit quality traits. In addition, we constructed iCitrus (http://wiki.bioinformatics.ucdavis.edu/index.php/ICitrus), a “functional database” that is essentially a web interface to a look-up table that allows users to use functional annotations in the web to identify poorly annotated citrus proteins. This resource will serve as a tool for growers and field extension specialists.
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Or, Etti, David Galbraith, and Anne Fennell. Exploring mechanisms involved in grape bud dormancy: Large-scale analysis of expression reprogramming following controlled dormancy induction and dormancy release. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7587232.bard.
Full textAbstract:
The timing of dormancy induction and release is very important to the economic production of table grape. Advances in manipulation of dormancy induction and dormancy release are dependent on the establishment of a comprehensive understanding of biological mechanisms involved in bud dormancy. To gain insight into these mechanisms we initiated the research that had two main objectives: A. Analyzing the expression profiles of large subsets of genes, following controlled dormancy induction and dormancy release, and assessing the role of known metabolic pathways, known regulatory genes and novel sequences involved in these processes B. Comparing expression profiles following the perception of various artificial as well as natural signals known to induce dormancy release, and searching for gene showing similar expression patterns, as candidates for further study of pathways having potential to play a central role in dormancy release. We first created targeted EST collections from V. vinifera and V. riparia mature buds. Clones were randomly selected from cDNA libraries prepared following controlled dormancy release and controlled dormancy induction and from respective controls. The entire collection (7920 vinifera and 1194 riparia clones) was sequenced and subjected to bioinformatics analysis, including clustering, annotations and GO classifications. PCR products from the entire collection were used for printing of cDNA microarrays. Bud tissue in general, and the dormant bud in particular, are under-represented within the grape EST database. Accordingly, 59% of the our vinifera EST collection, composed of 5516 unigenes, are not included within the current Vitis TIGR collection and about 22% of these transcripts bear no resemblance to any known plant transcript, corroborating the current need for our targeted EST collection and the bud specific cDNA array. Analysis of the V. riparia sequences yielded 814 unigenes, of which 140 are unique (keilin et al., manuscript, Appendix B). Results from computational expression profiling of the vinifera collection suggest that oxidative stress, calcium signaling, intracellular vesicle trafficking and anaerobic mode of carbohydrate metabolism play a role in the regulation and execution of grape-bud dormancy release. A comprehensive analysis confirmed the induction of transcription from several calcium–signaling related genes following HC treatment, and detected an inhibiting effect of calcium channel blocker and calcium chelator on HC-induced and chilling-induced bud break. It also detected the existence of HC-induced and calcium dependent protein phosphorylation activity. These data suggest, for the first time, that calcium signaling is involved in the mechanism of dormancy release (Pang et al., in preparation). We compared the effects of heat shock (HS) to those detected in buds following HC application and found that HS lead to earlier and higher bud break. We also demonstrated similar temporary reduction in catalase expression and temporary induction of ascorbate peroxidase, glutathione reductase, thioredoxin and glutathione S transferase expression following both treatments. These findings further support the assumption that temporary oxidative stress is part of the mechanism leading to bud break. The temporary induction of sucrose syntase, pyruvate decarboxylase and alcohol dehydrogenase indicate that temporary respiratory stress is developed and suggest that mitochondrial function may be of central importance for that mechanism. These finding, suggesting triggering of identical mechanisms by HS and HC, justified the comparison of expression profiles of HC and HS treated buds, as a tool for the identification of pathways with a central role in dormancy release (Halaly et al., in preparation). RNA samples from buds treated with HS, HC and water were hybridized with the cDNA arrays in an interconnected loop design. Differentially expressed genes from the were selected using R-language package from Bioconductor project called LIMMA and clones showing a significant change following both HS and HC treatments, compared to control, were selected for further analysis. A total of 1541 clones show significant induction, of which 37% have no hit or unknown function and the rest represent 661 genes with identified function. Similarly, out of 1452 clones showing significant reduction, only 53% of the clones have identified function and they represent 573 genes. The 661 induced genes are involved in 445 different molecular functions. About 90% of those functions were classified to 20 categories based on careful survey of the literature. Among other things, it appears that carbohydrate metabolism and mitochondrial function may be of central importance in the mechanism of dormancy release and studies in this direction are ongoing. Analysis of the reduced function is ongoing (Appendix A). A second set of hybridizations was carried out with RNA samples from buds exposed to short photoperiod, leading to induction of bud dormancy, and long photoperiod treatment, as control. Analysis indicated that 42 genes were significant difference between LD and SD and 11 of these were unique.