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Tesi sul tema "Summarization"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

Bosma, Wauter Eduard. "Discourse oriented summarization." Enschede : Centre for Telematics and Information Technology (CTIT), 2008. http://doc.utwente.nl/58836.

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2

Moon, Brandon B. "Interactive football summarization /." Diss., CLICK HERE for online access, 2010. http://contentdm.lib.byu.edu/ETD/image/etd3337.pdf.

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3

Moon, Brandon B. "Interactive Football Summarization." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/1999.

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Football fans do not have the time to watch every game in its entirety and need an effective solution that summarizes them the story of the game. Human-generated summaries are often too short, requiring time and resources to create. We utilize the advantages of Interactive TV to create an automatic football summarization service that is cohesive, provides context, covers the necessary plays, and is concise. First, we construct a degree of interest function that ranks each play based on detailed, play-by-play game events as well as viewing statistics collected from an interactive viewing enviro

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4

Sizov, Gleb. "Extraction-Based Automatic Summarization : Theoretical and Empirical Investigation of Summarization Techniques." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10861.

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<p>A summary is a shortened version of a text that contains the main points of the original content. Automatic summarization is the task of generating a summary by a computer. For example, given a collection of news articles for the last week an automatic summarizer is able to create a concise overview of the important events. This summary can be used as the replacement for the original content or help to identify the events that a person is particularly interested in. Potentially, automatic summarization can save a lot of time for people that deal with a large amount of textual information. T

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5

Chellal, Abdelhamid. "Event summarization on social media stream : retrospective and prospective tweet summarization." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30118/document.

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Le contenu généré dans les médias sociaux comme Twitter permet aux utilisateurs d'avoir un aperçu rétrospectif d'évènement et de suivre les nouveaux développements dès qu'ils se produisent. Cependant, bien que Twitter soit une source d'information importante, il est caractérisé par le volume et la vélocité des informations publiées qui rendent difficile le suivi de l'évolution des évènements. Pour permettre de mieux tirer profit de ce nouveau vecteur d'information, deux tâches complémentaires de recherche d'information dans les médias sociaux ont été introduites : la génération de résumé rétro

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6

Nahnsen, Thade. "Automation of summarization evaluation methods and their application to the summarization process." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5278.

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Summarization is the process of creating a more compact textual representation of a document or a collection of documents. In view of the vast increase in electronically available information sources in the last decade, filters such as automatically generated summaries are becoming ever more important to facilitate the efficient acquisition and use of required information. Different methods using natural language processing (NLP) techniques are being used to this end. One of the shallowest approaches is the clustering of available documents and the representation of the resulting clusters by o

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7

Smith, Christian. "Automatic summarization and readability." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68332.

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The enormous amount of information available today within different media gives rise to the notion of ways to reduce the inevitable complexity and to distribute text material to different channels or media. In an effort to investigate the possibilities of a tool to help eleviate the problem, an automatic summarizer called COGSUM has been developed and evaluated with regards to the informational quality of the summaries and with regards to the readability. COGSUM is based on word space methodology, including virtues such as problematic computational complexity and possibilities of inferring sem

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8

Seidlhofer, Barbara. "Discourse analysis for summarization." Thesis, University College London (University of London), 1991. http://discovery.ucl.ac.uk/10018780/.

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Summarization is an activity which language students are frequently called upon to perform, often without any explicit guidance. In a wider sense, it might be said that all learning, whether of language or anything else, involves the ability to distinguish what is important from what is not, and to incorporate it into existing schematic knowledge. In this respect, summarization can be seen as central to education in general as well as language education in particular. This thesis is an attempt to gain insights into the essential criteria for summarization. After the first chapter has outlined

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9

Ceylan, Hakan. "Investigating the Extractive Summarization of Literary Novels." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc103298/.

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Abstract Due to the vast amount of information we are faced with, summarization has become a critical necessity of everyday human life. Given that a large fraction of the electronic documents available online and elsewhere consist of short texts such as Web pages, news articles, scientific reports, and others, the focus of natural language processing techniques to date has been on the automation of methods targeting short documents. We are witnessing however a change: an increasingly larger number of books become available in electronic format. This means that the need for language process

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10

Demirtas, Kezban. "Automatic Video Categorization And Summarization." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611113/index.pdf.

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In this thesis, we make automatic video categorization and summarization by using subtitles of videos. We propose two methods for video categorization. The first method makes unsupervised categorization by applying natural language processing techniques on video subtitles and uses the WordNet lexical database and WordNet domains. The method starts with text preprocessing. Then a keyword extraction algorithm and a word sense disambiguation method are applied. The WordNet domains that correspond to the correct senses of keywords are extracted. Video is assigned a category label based on the extr

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11

Kazantseva, Anna. "Automatic summarization of short fiction." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27861.

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This work is an inquiry into automatic summarization of short of fiction. In this dissertation, I present a system that composes summaries of literary short stories employing two types of information: information about entities central to a story and information about the grammatical aspect of clauses. The summaries are tailored to a specific purpose: helping a reader decide whether she would be interested in reading a particular story. They contain just enough information to enable a reader to form adequate expectations about the story, but they do not reveal the plot. According to these crit

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12

Wen, Chung-Lin S. M. Massachusetts Institute of Technology. "Event-centric Twitter photo summarization." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91417.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.<br>40<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 71-74).<br>We develop a novel algorithm based on spectral geometry that summarize a photo collection into a small subset that represents the collection well. While the definition for a good summarization might not be unique, we focus on two metrics in this thesis: representativeness and diversity. By representativeness we mean that the sampled photo should be similar to ot

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13

Branavan, Satchuthananthavale Rasiah Kuhan. "High compression rate text summarization." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44368.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.<br>Includes bibliographical references (p. 95-97).<br>This thesis focuses on methods for condensing large documents into highly concise summaries, achieving compression rates on par with human writers. While the need for such summaries in the current age of information overload is increasing, the desired compression rate has thus far been beyond the reach of automatic summarization systems. The potency of our summarization methods is due to their in-depth modelling of document cont

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14

LI, WEI. "HIERARCHICAL SUMMARIZATION OF VIDEO DATA." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1186941444.

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15

Subramanian, Hema. "Summarization Of Real Valued Biclusters." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307442728.

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16

Karlbom, Hannes. "Abstractive Summarization of Podcast Transcriptions." Thesis, Uppsala universitet, Artificiell intelligens, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-443377.

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In the rapidly growing medium of podcasts, as episodes are automatically transcribed the need for good natural language summarization models which can handle a variety of obstacles presented by the transcriptions and the format has increased. This thesis investigates the transformer-based sequence-to-sequence models, where an attention mechanism keeps track of which words in the context are most important to the next word prediction in the sequence. Different summarization models are investigated on a large-scale open-domain podcast dataset which presents challenges such as transcription error

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17

Linhares, Pontes Elvys. "Compressive Cross-Language Text Summarization." Thesis, Avignon, 2018. http://www.theses.fr/2018AVIG0232/document.

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La popularisation des réseaux sociaux et des documents numériques a rapidement accru l'information disponible sur Internet. Cependant, cette quantité massive de données ne peut pas être analysée manuellement. Parmi les applications existantes du Traitement Automatique du Langage Naturel (TALN), nous nous intéressons dans cette thèse au résumé cross-lingue de texte, autrement dit à la production de résumés dans une langue différente de celle des documents sources. Nous analysons également d'autres tâches du TALN (la représentation des mots, la similarité sémantique ou encore la compression de p

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18

Wu, Jiewen. "WHISK: Web Hosted Information into Summarized Knowledge." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1633.

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Abstract (sommario):

Today’s online content increases at an alarmingly rate which exceeds users’ ability to consume such content. Modern search techniques allow users to enter keyword queries to find content they wish to see. However, such techniques break down when users freely browse the internet without knowing exactly what they want. Users may have to invest an unnecessarily long time reading content to see if they are interested in it. Automatic text summarization helps relieve this problem by creating synopses that significantly reduce the text while preserving the key points. Steffen Lyngbaek created the SP

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19

Ozsoy, Makbule Gulcin. "Text Summarization Using Latent Semantic Analysis." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612988/index.pdf.

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Text summarization solves the problem of presenting the information needed by a user in a compact form. There are different approaches to create well formed summaries in literature. One of the newest methods in text summarization is the Latent Semantic Analysis (LSA) method. In this thesis, different LSA based summarization algorithms are explained and two new LSA based summarization algorithms are proposed. The algorithms are evaluated on Turkish and English documents, and their performances are compared using their ROUGE scores.

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20

Oya, Tatsuro. "Automatic abstractive summarization of meeting conversations." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/49946.

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Nowadays, there are various ways for people to share and exchange information. Phone calls, E-mails, and social networking applications are tools which have made it much easier for us to communicate. Despite the existence of these convenient methods for exchanging ideas, meetings are still one of the most important ways for people to collaborate, share information, discuss their plans, and make decisions for their organizations. However, some drawbacks exist to them as well. Generally, meetings are time consuming and require the participation of all members. Taking meeting minutes for the bene

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21

Liu, Qing Computer Science &amp Engineering Faculty of Engineering UNSW. "Summarization of very large spatial dataset." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/25489.

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Nowadays there are a large number of applications, such as digital library information retrieval, business data analysis, CAD/CAM, multimedia applications with images and sound, real-time process control and scientific computation, with data sets about gigabytes, terabytes or even petabytes. Because data distributions are too large to be stored accurately, maintaining compact and accurate summarized information about underlying data is of crucial important. The summarizing problem for Level 1 (disjoint and non-disjoint) topological relationship has been well studied for the past few years. Ho

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22

Mlynarski, Angela, and University of Lethbridge Faculty of Arts and Science. "Automatic text summarization in digital libraries." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2006, 2006. http://hdl.handle.net/10133/270.

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A digital library is a collection of services and information objects for storing, accessing, and retrieving digital objects. Automatic text summarization presents salient information in a condensed form suitable for user needs. This thesis amalgamates digital libraries and automatic text summarization by extending the Greenstone Digital Library software suite to include the University of Lethbridge Summarizer. The tool generates summaries, nouns, and non phrases for use as metadata for searching and browsing digital collections. Digital collections of newspapers, PDFs, and eBooks were created

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23

Sanchan, Nattapong. "Domain-focused summarization of polarized debates." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/20878/.

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Due to the exponential growth of Internet use, textual content is increasingly published in online media. In everyday, more and more news content, blog posts, and scientific articles are published to the online volumes and thus open doors for the text summarization research community to conduct research on those areas. Whilst there are freely accessible repositories for such content, online debates which have recently become popular have remained largely unexplored. This thesis addresses the challenge in applying text summarization to summarize online debates. We view that the task of summariz

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24

Singi, Reddy Dinesh Reddy. "Comparative text summarization of product reviews." Thesis, Kansas State University, 2010. http://hdl.handle.net/2097/7031.

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Master of Science<br>Department of Computing and Information Sciences<br>William H. Hsu<br>This thesis presents an approach towards summarizing product reviews using comparative sentences by sentiment analysis. Specifically, we consider the problem of extracting and scoring features from natural language text for qualitative reviews in a particular domain. When shopping for a product, customers do not find sufficient time to learn about all products on the market. Similarly, manufacturers do not have proper written sources from which to learn about customer opinions. The only available techn

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25

Tohalino, Jorge Andoni Valverde. "Extractive document summarization using complex networks." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-24102018-155954/.

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Due to a large amount of textual information available on the Internet, the task of automatic document summarization has gained significant importance. Document summarization became important because its focus is the development of techniques aimed at finding relevant and concise content in large volumes of information without changing its original meaning. The purpose of this Masters work is to use network theory concepts for extractive document summarization for both Single Document Summarization (SDS) and Multi-Document Summarization (MDS). In this work, the documents are modeled as network

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26

AGUIAR, C. Z. "Concept Maps Mining for Text Summarization." Universidade Federal do Espírito Santo, 2017. http://repositorio.ufes.br/handle/10/9846.

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Made available in DSpace on 2018-08-02T00:03:48Z (GMT). No. of bitstreams: 1 tese_11160_CamilaZacche_dissertacao_final.pdf: 5437260 bytes, checksum: 0c96c6b2cce9c15ea234627fad78ac9a (MD5) Previous issue date: 2017-03-31<br>8 Resumo Os mapas conceituais são ferramentas gráficas para a representação e construção do conhecimento. Conceitos e relações formam a base para o aprendizado e, portanto, os mapas conceituais têm sido amplamente utilizados em diferentes situações e para diferentes propósitos na educação, sendo uma delas a represent ação do texto escrito. Mes mo um

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27

O'Brien, Shayne S. M. Massachusetts Institute of Technology. "Unsupervised summarization of public talk radio." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123648.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 111-118).<br>Talk radio exerts significant influence on the political and social dynamics of the United States, but labor-intensive data collection and curation processes have prevented previous works from analyzing its content at scale. Over the past year, the Laboratory for Social Machines and Cortico have created an ingest system to record and automatically transcribe audio fr

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28

Pham, Quang-Khai. "Time Sequence Summarization: Theory and Applications." Phd thesis, Université de Nantes, 2010. http://tel.archives-ouvertes.fr/tel-00538512.

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Les domaines de la médecine, du web, du commerce ou de la nance génèrent et stockent de grandes masses d'information sous la forme de séquences d'événements. Ces archives représentent des sources d'information très riches pour des analystes avides d'y découvrir des perles de connaissance. Par exemple, les biologistes cherchent à découvrir les facteurs de risque d'une maladie en analysant l'historique des patients, les producteurs de contenu web et les bureaux de marketing examinent les habitudes de consommation des clients et les opérateurs boursiers suivent les évolutions du marché pour mieux

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29

Pham, Quang-Khai. "Time sequence summarization : theory and applications." Phd thesis, Nantes, 2010. http://www.theses.fr/2010NANT2102.

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Abstract (sommario):

Les domaines de la médecine, du web, du commerce ou de la nance génèrent et stockent de grandes masses d'information sous la forme de séquences d'événements. Ces archives représentent des sources d'information très riches pour des analystes avides d'y découvrir des perles de connaissance. Par exemple, les biologistes cherchent à découvrir les facteurs de risque d'une maladie en analysant l'historique des patients, les producteurs de contenu web et les bureaux de marketing examinent les habitudes de consommation des clients et les opérateurs boursiers suivent les évolutions du marché pour mieux

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30

Niccolai, Lorenzo. "Distillation Knowledge applied on Pegasus for Summarization." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22202/.

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In the scope of Natural Language Processing one of the most intricate tasks is Text Summarization, in human terms: writing an essay. Something that we learn in primary school is yet very difficult to reproduce for a machine, it was almost impossible before the advent of Deep Learning. The trending technology to face up Summarization - and every task that involves generating text - is the Transformer. This thesis aims to experiment what entails reducing the complexity of Pegasus, a huge state-of-the-art model based on Transformers. Through a technique called Knowledge Distillation the original

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31

Casamayor, Gerard. "Semantically-oriented text planning for automatic summarization." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/671530.

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Text summarization deals with the automatic creation of summaries from one or more documents, either by extracting fragments from the input text or by generating an abstract de novo. Research in recent years has become dominated by a new paradigm where summarization is addressed as a mapping from a sequence of tokens in an input document to a new sequence of tokens summarizing the input. Works following this paradigm apply supervised deep learning methods to learn sequence to sequence models from a large corpus of documents paired with human-crafted summaries. Despite impressive results in aut

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32

Reeve, Lawrence H. Han Hyoil. "Semantic annotation and summarization of biomedical text /." Philadelphia, Pa. : Drexel University, 2007. http://hdl.handle.net/1860/1779.

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33

Hassel, Martin. "Resource Lean and Portable Automatic Text Summarization." Doctoral thesis, Stockholm : Numerisk analys och datalogi Numerical Analysis and Computer Science, Kungliga Tekniska högskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4414.

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34

Ulrich, Jan. "Supervised machine learning for email thread summarization." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2363.

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Email has become a part of most people's lives, and the ever increasing amount of messages people receive can lead to email overload. We attempt to mitigate this problem using email thread summarization. Summaries can be used for things other than just replacing an incoming email message. They can be used in the business world as a form of corporate memory, or to allow a new team member an easy way to catch up on an ongoing conversation. Email threads are of particular interest to summarization because they contain much structural redundancy due to their conversational nature. Our email threa

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35

Di, Fabrizzio Giuseppe. "Automatic summarization of opinions in service reviews." Thesis, University of Sheffield, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.632550.

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36

"Fractal summarization." 2003. http://library.cuhk.edu.hk/record=b6073565.

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Wang Fu Lee.<br>"August 2003."<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 2003.<br>Includes bibliographical references (p. 256-281).<br>Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Mode of access: World Wide Web.<br>Abstracts in English and Chinese.

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Costa, Vítor Manuel da. "Update Summarization." Master's thesis, 2014. https://repositorio-aberto.up.pt/handle/10216/77587.

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Costa, Vítor Manuel da. "Update Summarization." Dissertação, 2014. https://repositorio-aberto.up.pt/handle/10216/77587.

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39

Hassanlou, Nasrin. "Probabilistic graph summarization." Thesis, 2012. http://hdl.handle.net/1828/4403.

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We study group-summarization of probabilistic graphs that naturally arise in social networks, semistructured data, and other applications. Our proposed framework groups the nodes and edges of the graph based on a user selected set of node attributes. We present methods to compute useful graph aggregates without the need to create all of the possible graph-instances of the original probabilistic graph. Also, we present an algorithm for graph summarization based on pure relational (SQL) technology. We analyze our algorithm and practically evaluate its efficiency using an extended Epinions

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40

Ding, Wei-Ming, and 丁偉民. "Summarization Scoring System." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/41800171399131023093.

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碩士<br>國立臺灣師範大學<br>資訊教育學系<br>93<br>The main purpose of this research is to develop a summarization scoring system for the teacher of the elementary school. This system refers to a method called Latent Semantic Analysis(LSA), to use Singular Value Decomposition(SVD) to build the semantic space. We build several kinds of semantic spaces which the size and style of writing are different. To compare the keywords of the summarizations between the teacher and the students in the different semantic spaces for the scoring. In addition to scoring, we analyze the other indexes of the summarization scorin

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41

Chiu, Chung-Ren, and 邱中人. "Chinese News Summarization." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/12254466664744727912.

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42

Kumar, Trun. "Automaic Text Summarization." Thesis, 2014. http://ethesis.nitrkl.ac.in/5619/1/110CS0127.pdf.

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Automatic summarization is the procedure of decreasing the content of a document with a machine (computer) program so as to make a summary that holds the most critical sentences of the text file (document). Extracting summary from the document is a difficult task for human beings. Therefore to generate summary automatically has to facilitate several challenges; as the system automates it can only extract the required information from the original document. As the issue of information overload has grown - trouble has been initiated, and as the measure of data has extended, so has eagerness to c

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43

Kumar, T. "Automatic text summarization." Thesis, 2014. http://ethesis.nitrkl.ac.in/5617/1/E-65.pdf.

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Automatic summarization is the procedure of decreasing the content of a document with a machine (computer) program so as to make a summary that holds the most critical sentences of the text file (document). Extracting summary from the document is a difficult task for human beings. Therefore to generate summary automatically has to facilitate several challenges; as the system automates it can only extract the required information from the original document. As the issue of information overload has grown - trouble has been initiated, and as the measure of data has extended, so has eagerness to c

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44

Lee, Hsiang-Pin, and 李祥賓. "Text Summarization on News." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/54130654842944705212.

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碩士<br>東吳大學<br>資訊科學系<br>89<br>The swift development of information technique and the Internet has resulted in a problem of information overflow. Hence it is imperative to find a way to help users browse through documents efficiently and effectively. Text summarization could be a remedy to this problem. Traditional text summarization is usually processed manually. However, it does cost lots of human resources and cannot satisfy the demand in real time. Therefore, it is necessary to automate the process. This paper presents three methods of text summarization on Reuters news corpus. Fi

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Yang, Jeng-Yuan, and 楊政遠. "Statistical Chinese News Summarization." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/tu9p36.

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碩士<br>國立臺北科技大學<br>資訊工程系研究所<br>98<br>With the growing number of news articles around the world every day, it would be helpful to users if the time to read news articles can be reduced. Typically, there are two general ways to summarize documents: multi-document summarization and single-document summarization. Multi-document news summarization is similar to ‘hot topics of the week’, which only lists the most important news reports; while single-document news summarization is more similar to a short abstract, which help readers quickly grasp the overall idea in articles. The focus of single-docum

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Tsai, Jean Ya-Chin, and 蔡雅晴. "Comic-Styled Movie Summarization." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/88014021431825574473.

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碩士<br>國立臺灣大學<br>資訊管理學研究所<br>95<br>This paper intends to use comics as the form of presentation best for movie content summarization. Movies, with its powerful ability to convey stories and evoke emotions through moving frames, find a significant body of research and application in video content analysis field. However, while this art form has been widely investigated using existing video analysis technology, none of them has been able to produce story content summarization with pleasant or satisfactory results. Indeed, the comic form’s naturally rich visual story-telling vocabulary and vivi

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Cheng, Kun-You, and 成崑佑. "Content-oriented Video Summarization." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/09382153335369623907.

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碩士<br>國立東華大學<br>資訊工程學系<br>94<br>The paper presents a new framework of video summarization which can extract and summarize video shots that a user interests in from a long and complicated video, according to their similarity of motion type and scene. Firstly, the shot detection adopts the color and edge information to make shot boundaries accurate. Then the clustering process classifies the shots according to their similarities in scenes and motion types. Finally, we select the important shots of each cluster by estimating their priority value. The priority value determines the importance of ea

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沈健誠. "Multi-Document Summarization System." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/67547214470615254060.

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碩士<br>國立清華大學<br>資訊工程學系<br>89<br>Most summarization systems are designed for a single document at present. These systems indicate the essence of individual document, but do not transfer similar documents into single summary. Can we develop a multi-document summarization system, which transfers related documents with the same event into a summary? If that is possible, the main points of documents will be clearly and simply displayed with two or three sentences. Users can see whether these documents are what they want in a minute. It can reduce time for collecting documents and enable users to ga

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Tsai, Jean Ya-Chin. "Comic-Styled Movie Summarization." 2007. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-2307200715130800.

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Chou, Yu-Yu, and 周宥宇. "Spoken Document Summarization : with Structural Support Vector Machine，Domain Adaptation and Abstractive Summarization." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/48591868287184216440.

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