Journal articles: 'Entities on the Web'

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Efthymiou, Vasilis, Kostas Stefanidis, and Vassilis Christophides. "Benchmarking Blocking Algorithms for Web Entities." IEEE Transactions on Big Data 6, no. 2 (June 1, 2020): 382–95. http://dx.doi.org/10.1109/tbdata.2016.2576463.

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Huang, Xinyan, Xinjun Wang, and Hui Li. "Mining Similar Traces of Entities on Web." Cybernetics and Information Technologies 15, no. 6 (December 1, 2015): 219–29. http://dx.doi.org/10.1515/cait-2015-0081.

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Abstract Events about entities have been widely collected on Web, allowing us to analyze how peer entities interact and learn the relationships that exist among the entities. In this paper we investigate similar traces that have not been adequately studied so far. Intuitively, peer entities tend to have similar traces. The challenges in mining similar traces are: (1) the occurring time lags of traces are usually unknown and varying; (2) the existence of large-scale events of entities and complexity of the model representing all the events. In this paper we propose a simple, but practical method that addresses all these challenges. Firstly, sliding windows are adopted to filter out the significant events and then find the candidate topic sequences. Secondly, dynamic programming is employed to mine similar candidate topic sequences of entities. Finally, an efficient method is proposed to mine all the similar traces of entities. It is able to mine similar traces of peer entities with high accuracy. We conduct comprehensive experiments on synthetic datasets to demonstrate the efficiency of the method proposed.

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Thakare, Abhijeet Ramesh, and Parag S. Deshpande. "Comparative Search of Entities." International Journal of Software Engineering and Knowledge Engineering 27, no. 08 (October 2017): 1333–57. http://dx.doi.org/10.1142/s0218194017500498.

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Nowadays, every manufacturer or retailer displays their product information on various websites. The customer has to visit, the number of such web pages to choose the right product, because the information is not available at one place. There are some websites that show such information in one place, but they are product specific and in general information is manually updated. In this paper, we propose a novel concept of web-spreadsheet, which displays product information by crawling through related web pages and generates information like a spreadsheet where each row represents product information and each column represents product attributes. We are extracting the product name of specified product class using decision tree-based classifier by features obtained using Part of Speech (POS) tagging and distance measure. It also extracts the value-measure pairs of preset attributes using distance measure, POS tagging and Data type. This approach will save a lot of time of comparing different products and customers need not have to scan a number of websites for comparison. We present promising results in various product classes which surpass many existing techniques in the literature. The proposed method can work accurately without initial trained labeled data which is expensive to obtain.

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Yin Ming, Ming, Dion Hoe‐lian Goh, Ee‐Peng Lim, and Aixin Sun. "Discovery of concept entities from web sites using web unit mining." International Journal of Web Information Systems 1, no. 3 (August 2005): 123–36. http://dx.doi.org/10.1108/17440080580000088.

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Jang, Myungha, Jin-woo Park, and Seung-won Hwang. "Predictive Mining of Comparable Entities from the Web." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 66–72. http://dx.doi.org/10.1609/aaai.v26i1.8112.

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Comparing entities is an important part of decision making. Several approaches have been reported for mining comparable entities from Web sources to improve user experience in comparing entities online.However, these efforts extract only entities explicitly compared in the corpora, and may exclude entities that occur less-frequently but potentially comparable. To build a more complete comparison machine that can infer such missing relations, here we develop a solutionto predict transitivity of known comparable relations. Named CliqueGrow, our approach predicts missing links given a comparable entity graph obtained from versus query logs. Our approach achieved the highest F1-score among five link prediction approaches and a commercial comparison engine provided by Yahoo!.

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Barbosa, Luciano. "Learning representations of Web entities for entity resolution." International Journal of Web Information Systems 15, no. 3 (August 19, 2019): 346–58. http://dx.doi.org/10.1108/ijwis-07-2018-0059.

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Purpose Matching instances of the same entity, a task known as entity resolution, is a key step in the process of data integration. This paper aims to propose a deep learning network that learns different representations of Web entities for entity resolution. Design/methodology/approach To match Web entities, the proposed network learns the following representations of entities: embeddings, which are vector representations of the words in the entities in a low-dimensional space; convolutional vectors from a convolutional layer, which capture short-distance patterns in word sequences in the entities; and bag-of-word vectors, created by a bow layer that learns weights for words in the vocabulary based on the task at hand. Given a pair of entities, the similarity between their learned representations is used as a feature to a binary classifier that identifies a possible match. In addition to those features, the classifier also uses a modification of inverse document frequency for pairs, which identifies discriminative words in pairs of entities. Findings The proposed approach was evaluated in two commercial and two academic entity resolution benchmarking data sets. The results have shown that the proposed strategy outperforms previous approaches in the commercial data sets, which are more challenging, and have similar results to its competitors in the academic data sets. Originality/value No previous work has used a single deep learning framework to learn different representations of Web entities for entity resolution.

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Dai, Hong-Jie, Chi-Hsin Huang, Ryan T. K. Lin, Richard Tzong-Han Tsai, and Wen-Lian Hsu. "BIOSMILE web search: a web application for annotating biomedical entities and relations." Nucleic Acids Research 36, suppl_2 (May 31, 2008): W390—W398. http://dx.doi.org/10.1093/nar/gkn319.

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Sung, Ki-Youn, and Bo-Hyun Yun. "Topic based Web Document Clustering using Named Entities." Journal of the Korea Contents Association 10, no. 5 (May 28, 2010): 29–36. http://dx.doi.org/10.5392/jkca.2010.10.5.029.

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Presutti, Valentina, and Aldo Gangemi. "Identity of Resources and Entities on the Web." International Journal on Semantic Web and Information Systems 4, no. 2 (April 2008): 49–72. http://dx.doi.org/10.4018/jswis.2008040103.

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Köpcke, Hanna, Andreas Thor, and Erhard Rahm. "Learning-Based Approaches for Matching Web Data Entities." IEEE Internet Computing 14, no. 4 (July 2010): 23–31. http://dx.doi.org/10.1109/mic.2010.58.

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Toll, D. G., and A. C. Cubitt. "Representing geotechnical entities on the World Wide Web." Advances in Engineering Software 34, no. 11-12 (December 2003): 729–36. http://dx.doi.org/10.1016/s0965-9978(03)00097-8.

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Muñoz, David, Fernando Pérez-Téllez, and David Pinto. "A Web-based Tagger for Named Entities Detection." Research in Computing Science 148, no. 3 (December 31, 2019): 227–43. http://dx.doi.org/10.13053/rcs-148-3-19.

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Kang, Changsung, Dawei Yin, Ruiqiang Zhang, Nicolas Torzec, Jianzhang He, and Yi Chang. "Learning to rank related entities in Web search." Neurocomputing 166 (October 2015): 309–18. http://dx.doi.org/10.1016/j.neucom.2015.04.004.

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Sun, Aixin, Ying Liu, and Ee-Peng Lim. "Web classification of conceptual entities using co-training." Expert Systems with Applications 38, no. 12 (November 2011): 14367–75. http://dx.doi.org/10.1016/j.eswa.2011.03.010.

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Wang, Puwei, Zhi Jin, Lin Liu, and Budan Wu. "Specifying and Composing Web Services with an Environment Ontology-Based Approach." International Journal of Web Services Research 7, no. 3 (July 2010): 73–92. http://dx.doi.org/10.4018/jwsr.2010070104.

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Precise capability specification is the key for identifying and composing the right Web services. This paper specifies service capabilities in terms of the environment entities from the application domain and the effects imposed by the Web service on these entities. An environment ontology for Web services is adopted to provide formal sharable representations of the domain-specific environment entities. A hierarchical state machine is constructed for each environment entity to describe its behaviors, and the effects imposed by a Web service are described as the state transitions traces of environment entities, which define the capability of the Web service. Web service composition that satisfies a set of requested effects is then conducted by reasoning on the effects of services. The proposed approach emphasizes the external manifestation of Web services and service composition based on the effect reasoning. An example of online travel service illustrates the proposed approach.

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Bouquet, Paolo, Heiko Stoermer, and Massimiliano Vignolo. "Web of Data and Web of Entities: Identity and Reference in Interlinked Data in the Semantic Web." Philosophy & Technology 25, no. 1 (January 12, 2011): 5–26. http://dx.doi.org/10.1007/s13347-010-0011-6.

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Verstein, Andrew. "Enterprise Without Entities." Michigan Law Review, no. 116.2 (2017): 247. http://dx.doi.org/10.36644/mlr.116.2.enterprise.

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Scholars and practicing lawyers alike consider legal entities to be essential. Who can imagine running a large business without using a business organization, such as a corporation or partnership? This Article challenges conventional wisdom by showing that vast enterprises—with millions of customers paying trillions of dollars—often operate without any meaningful use of entities. This Article introduces the reciprocal exchange, a type of insurance company that operates without any meaningful use of a legal entity. Instead of obtaining insurance from a common nexus of contract, customers directly insure one another through a dense web of bilateral agreements. While often overlooked or conflated with mutual insurance companies, reciprocal exchanges include some of America’s largest and best-known insurance enterprises. This Article explores how it is possible to run an international conglomerate with essentially no recourse to organizational law as it is normally conceived, and it then draws out the important implications of these findings. The viability of reciprocal exchanges stands as a powerful foil to the academic consensus that legal entities are somehow essential, while nevertheless validating the underlying logic that led scholars to elevate entities in the first place.

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Bourseau, S., B. Bastens, and P. Leclercq. "Umbilical spider’s web." Acta Gastro Enterologica Belgica 85, no. 3 (September 2022): 542. http://dx.doi.org/10.51821/85.3.10418.

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Question: We report the case of a 38y old woman who consulted for chronic diffuse abdominal pain related to previous irritable bowel syndrome diagnosis. Physical examination showed nonblanching reddish hyperpigmented reticular peri-umbilical skin patch (figure 1). What’s your diagnosis? Answer: The diagnosis of erythema ab igne was made. Additional investigations confirmed repeated use of hot water bottles applied on abdominal wall for 3 weeks overnight for pain relief. Erythema ab igne is a pathognomonic cutaneous presentation of long-lasting exposure to heat sources (1). The pathophysiology of erythema ab igne remains uncertain. It has been suggested that heat exposure damages dermal vascular plexus and subsequent hemosiderin deposition leading to spider’s web-like hyperpigmentation. Differential diagnosis of peri -umbilical dermatological manifestations includes digestive-related entities as caput medusae’s sign (related to portal hypertension), Cullen’s sign or Walzel’s sign (related to acute pancreatitis); and non-digestive-related entities such as livedo reticularis (2). Erythema ab igne is well known from the dermatologists, mostly located on the lower limbs due to prolonged close exposition to heaters or on thighs due to laptop batteries (3). Erythema ab igne is usually of benign course, most often self-resolving after heat exposure discontinuation (3). We believe that it is of paramount to take into consideration the patients’ pain and to propose an adapted management to avoid self-treatment.

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Limaye, Girija, Sunita Sarawagi, and Soumen Chakrabarti. "Annotating and searching web tables using entities, types and relationships." Proceedings of the VLDB Endowment 3, no. 1-2 (September 2010): 1338–47. http://dx.doi.org/10.14778/1920841.1921005.

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Zosimov, V. V., O. V. Khrystodorov, and O. S. Bulgakova. "Technology of Web Applications Based On The Cyber-Entities Identification." Upravlâûŝie sistemy i mašiny, no. 3 (275) (November 20, 2018): 51–59. http://dx.doi.org/10.15407/usim.2018.03.051.

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Uyar, Ahmet, and Rabia Karapinar. "Investigating the precision of Web image search engines for popular and less popular entities." Journal of Information Science 43, no. 3 (April 1, 2016): 378–92. http://dx.doi.org/10.1177/0165551516642929.

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Image search is the second most frequently used search service on the Web. However, there are very few studies investigating any aspect of it. In this study, we investigate the precision of Web image search engines of Google and Bing for popular and less popular entities using text-based queries. Furthermore, we investigate four additional aspects of Web image search engines that have not been studied before. We used 60 different queries in total from three different domains for popular and less popular categories. We examined the relevancy of the top 100 images for each query. Our results indicate that image search is a solved problem for popular entities. They deliver 97% precision on the average for popular entities. However, precision values are much lower for less popular entities. For the top 100 results, average precision is 48% for Google and 33% for Bing. The most important problem seems to be the worst cases in which the precision can be less than 10%. The results show that significant improvement is needed to better identify relevant images for less popular entities. One of the main issues is the association problem. When a Web page has query words and multiple images, both Google and Bing are having difficulty determining the relevant images.

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Abbasi, Burhan Ud Din, Iram Fatima, Hamid Mukhtar, Sharifullah Khan, Abdulaziz Alhumam, and Hafiz Farooq Ahmad. "Autonomous schema markups based on intelligent computing for search engine optimization." PeerJ Computer Science 8 (December 8, 2022): e1163. http://dx.doi.org/10.7717/peerj-cs.1163.

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With advances in artificial intelligence and semantic technology, search engines are integrating semantics to address complex search queries to improve the results. This requires identification of well-known concepts or entities and their relationship from web page contents. But the increase in complex unstructured data on web pages has made the task of concept identification overly complex. Existing research focuses on entity recognition from the perspective of linguistic structures such as complete sentences and paragraphs, whereas a huge part of the data on web pages exists as unstructured text fragments enclosed in HTML tags. Ontologies provide schemas to structure the data on the web. However, including them in the web pages requires additional resources and expertise from organizations or webmasters and thus becoming a major hindrance in their large-scale adoption. We propose an approach for autonomous identification of entities from short text present in web pages to populate semantic models based on a specific ontology model. The proposed approach has been applied to a public dataset containing academic web pages. We employ a long short-term memory (LSTM) deep learning network and the random forest machine learning algorithm to predict entities. The proposed methodology gives an overall accuracy of 0.94 on the test dataset, indicating a potential for automated prediction even in the case of a limited number of training samples for various entities, thus, significantly reducing the required manual workload in practical applications.

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Pirró, Giuseppe. "REWOrD: Semantic Relatedness in the Web of Data." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 129–35. http://dx.doi.org/10.1609/aaai.v26i1.8107.

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This paper presents REWOrD, an approach to compute semantic relatedness between entities in the Web of Data representing real word concepts. REWOrD exploits the graph nature of RDF data and the SPARQL query language to access this data. Through simple queries, REWOrD constructs weighted vectors keeping the informativeness of RDF predicates used to make statements about the entities being compared. The most informative path is also considered to further refine informativeness. Relatedness is then computed by the cosine of the weighted vectors. Differently from previous approaches based on Wikipedia, REWOrD does not require any prepro- cessing or custom data transformation. Indeed, it can lever- age whatever RDF knowledge base as a source of background knowledge. We evaluated REWOrD in different settings by using a new dataset of real word entities and investigate its flexibility. As compared to related work on classical datasets, REWOrD obtains comparable results while, on one side, it avoids the burden of preprocessing and data transformation and, on the other side, it provides more flexibility and applicability in a broad range of domains.

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Yu, Li, Peiyuan Qiu, Jialiang Gao, and Feng Lu. "A Knowledge-Based Filtering Method for Open Relations among Geo-Entities." ISPRS International Journal of Geo-Information 8, no. 2 (January 28, 2019): 59. http://dx.doi.org/10.3390/ijgi8020059.

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Knowledge graphs (KGs) are crucial resources for supporting geographical knowledge services. Given the vast geographical knowledge in web text, extraction of geo-entity relations from web text has become the core technology for construction of geographical KGs; furthermore, it directly affects the quality of geographical knowledge services. However, web text inevitably contains noise and geographical knowledge can be sparsely distributed, both of which greatly restrict the quality of geo-entity relationship extraction. We propose a method for filtering geo-entity relations based on existing knowledge bases (KBs). Accordingly, ontology knowledge, fact knowledge, and synonym knowledge are integrated to generate geo-related knowledge. Then, the extracted geo-entity relationships and the geo-related knowledge are transferred into vectors, and the maximum similarity between vectors is the confidence value of one extracted geo-entity relationship triple. Our method takes full advantage of existing KBs to assess the quality of geographical information in web text, which is helpful to improve the richness and freshness of geographical KGs. Compared with the Stanford OpenIE method, our method decreased the mean square error (MSE) from 0.62 to 0.06 in the confidence interval [0.7, 1], and improved the area under the receiver operating characteristic (ROC) curve (AUC) from 0.51 to 0.89.

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Zhang, Chuxu, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, and Nitesh V. Chawla. "Inductive Contextual Relation Learning for Personalization." ACM Transactions on Information Systems 39, no. 3 (May 22, 2021): 1–22. http://dx.doi.org/10.1145/3450353.

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Web personalization, e.g., recommendation or relevance search, tailoring a service/product to accommodate specific online users, is becoming increasingly important. Inductive personalization aims to infer the relations between existing entities and unseen new ones, e.g., searching relevant authors for new papers or recommending new items to users. This problem, however, is challenging since most of recent studies focus on transductive problem for existing entities. In addition, despite some inductive learning approaches have been introduced recently, their performance is sub-optimal due to relatively simple and inflexible architectures for aggregating entity’s content. To this end, we propose the inductive contextual personalization (ICP) framework through contextual relation learning. Specifically, we first formulate the pairwise relations between entities with a ranking optimization scheme that employs neural aggregator to fuse entity’s heterogeneous contents. Next, we introduce a node embedding term to capture entity’s contextual relations, as a smoothness constraint over the prior ranking objective. Finally, the gradient descent procedure with adaptive negative sampling is employed to learn the model parameters. The learned model is capable of inferring the relations between existing entities and inductive ones. Thorough experiments demonstrate that ICP outperforms numerous baseline methods for two different applications, i.e., relevant author search and new item recommendation.

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DIX, ALAN, AKRIVI KATIFORI, GIORGOS LEPOURAS, COSTAS VASSILAKIS, and NADEEM SHABIR. "SPREADING ACTIVATION OVER ONTOLOGY-BASED RESOURCES: FROM PERSONAL CONTEXT TO WEB SCALE REASONING." International Journal of Semantic Computing 04, no. 01 (March 2010): 59–102. http://dx.doi.org/10.1142/s1793351x10000973.

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This paper describes methods to allow spreading activation to be used on web-scale information resources. Existing work has shown that spreading activation can be used to model context over small personal ontologies, which can be used to assist in various user activities, for example, in auto-completing web forms. This previous work is extended and methods are developed by which large external repositories, including corporate information and the web, can be linked to the user's personal ontology and thus allow automated assistance that is able to draw on the entire web of data. The basic idea is to augment the personal ontology with cached data from external repositories, where the choice of data to fetch or discard is related to the level of activation of entities already in the personal ontology or cached data. This relies on the assumption that the working set of highly active entities is relatively small; empirical results are presented, which suggest these assumptions are likely to hold. Implications of the techniques are discussed for user interaction and for the social web. In addition, warm world reasoning is proposed, applying rule-based reasoning over activated entities, potentially merging symbolic and sub-symbolic reasoning over web-scale knowledge bases.

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Yu, Y. X., and L. Y. Wang. "Research of Information Retrieval Based on Web Semantic Similarity." Applied Mechanics and Materials 135-136 (October 2011): 753–58. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.753.

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An important research of information retrieval technology is how to express the intention of users accurately and make a sensible judgment on the semantic similarity between conceptual entities. A scheme is presented to calculate the semantic similarity, which takes multi-inheritance of entities and property values into consideration , and then optimizes the computing process based on the tree structure of inheritance relationship. When the instance multiple inheritances are relatively complex, the accuracy rate is more pronounced than existing methods. The experimental results show that the scheme proposed in this paper can calculate semantic similarity more accurately even in ontology-based knowledge base.

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Minton, Steven, Sofus Macskassy, Peter LaMonica, Kane See, Craig Knoblock, Greg Barish, Matthew Michelson, and Raymond Liuzzi. "Monitoring Entities in an Uncertain World: Entity Resolution and Referential Integrit." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 2 (August 11, 2011): 1681–88. http://dx.doi.org/10.1609/aaai.v25i2.18860.

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This paper describes a system to help intelligence analysts track and analyze information being published in multiple sources, particularly open sources on the Web. The system integrates technology for Web harvesting, natural language extraction, and network analytics, and allows analysts to view and explore the results via a Web application. One of the difficult problems we address is the entity resolution problem, which occurs when there are multiple, differing ways to refer to the same entity. The problem is particularly complex when noisy data is being aggregated over time, there is no clean master list of entities, and the entities under investigation are intentionally being deceptive. Our system must not only perform entity resolution with noisy data, but must also gracefully recover when entity resolution mistakes are subsequently corrected. We present a case study in arms trafficking that illustrates the issues, and describe how they are addressed.

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XU, Hongyan, Xiaowan DANG, Yong FENG, and Junping LI. "Method of Deep Web entities identification based on BP neural network." Journal of Computer Applications 33, no. 3 (September 25, 2013): 776–79. http://dx.doi.org/10.3724/sp.j.1087.2013.00776.

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Carlos, r閟 Tavera Romero, Jesus Hamilton Ortiz, Osamah Ibrahim Khalaf, and rea R韔s Prado. "Web Application Commercial Design for Financial Entities Based on Business Intelligence." Computers, Materials & Continua 67, no. 3 (2021): 3177–88. http://dx.doi.org/10.32604/cmc.2021.014738.

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Huang, Jizhou, Shiqiang Ding, Haifeng Wang, and Ting Liu. "Learning to Recommend Related Entities With Serendipity for Web Search Users." ACM Transactions on Asian and Low-Resource Language Information Processing 17, no. 3 (May 10, 2018): 1–22. http://dx.doi.org/10.1145/3185663.

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Kumar, N. Senthil, and Dinakaran Muruganantham. "Disambiguating the Twitter Stream Entities and Enhancing the Search Operation Using DBpedia Ontology." International Journal of Information Technology and Web Engineering 11, no. 2 (April 2016): 51–62. http://dx.doi.org/10.4018/ijitwe.2016040104.

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The web and social web is holding the huge amount of unstructured data and makes the searching processing more cumbersome. The principal task here is to migrate the unstructured data into the structured data through the appropriate utilization of named entity detections. The goal of the paper is to automatically build and store the deep knowledge base of important facts and construct the comprehensive details about the facts such as its related named entities, its semantic classes of the entities and its mutual relationship with its temporal context can be thoroughly analyzed and probed. In this paper, the authors have given and proposed the model to identify all the major interpretations of the named entities and effectively link them to the appropriate mentions of the knowledge base (DBpedia). They finally evaluate the approaches that uniquely identify the DBpedia URIs of the selected entities and eliminate the other candidate mentions of the entities based on the authority rankings of those candidate mentions.

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Yue, Zongliang, Christopher D. Willey, Anita B. Hjelmeland, and Jake Y. Chen. "BEERE: a web server for biomedical entity expansion, ranking and explorations." Nucleic Acids Research 47, W1 (May 22, 2019): W578—W586. http://dx.doi.org/10.1093/nar/gkz428.

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Abstract BEERE (Biomedical Entity Expansion, Ranking and Explorations) is a new web-based data analysis tool to help biomedical researchers characterize any input list of genes/proteins, biomedical terms or their combinations, i.e. ‘biomedical entities’, in the context of existing literature. Specifically, BEERE first aims to help users examine the credibility of known entity-to-entity associative or semantic relationships supported by database or literature references from the user input of a gene/term list. Then, it will help users uncover the relative importance of each entity—a gene or a term—within the user input by computing the ranking scores of all entities. At last, it will help users hypothesize new gene functions or genotype–phenotype associations by an interactive visual interface of constructed global entity relationship network. The output from BEERE includes: a list of the original entities matched with known relationships in databases; any expanded entities that may be generated from the analysis; the ranks and ranking scores reported with statistical significance for each entity; and an interactive graphical display of the gene or term network within data provenance annotations that link to external data sources. The web server is free and open to all users with no login requirement and can be accessed at http://discovery.informatics.uab.edu/beere/.

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Helmy, Tarek, and Saeed Al-Bukhitan. "Framework for Automatic Semantic Annotation of Arabic Websites." International Journal of Cooperative Information Systems 25, no. 01 (March 2016): 1650001. http://dx.doi.org/10.1142/s0218843016500015.

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In order to achieve the vision of the semantic Web, it is important to have enough amount of semantic content on the Web sources. To produce the semantic content on the existing Web, semantic annotation of the Web sources is required. Semantic annotation adds machine-readable content to the Web sources. Because the Web is growing at an exponential rate, semantic annotation by hand is not possible. In this paper, we present an Automatic Semantic Annotation Framework (ASAF) for semantic annotation of Arabic Web sources based on the domain ontologies. We present a learning approach that utilizes public Arabic resources, such as Wikipedia and WordNet for building Arabic ontologies. Moreover, we present different approaches for extracting name entities and relationships from Arabic Web sources. As a case study, we have developed and expanded a set of Arabic ontologies related to food, health, and nutrition through a set of processes. We have also developed the ASAF prototype, and showed how it can utilize these ontologies for extracting health, food related name entities, and relationships from the Web sources in order to annotate and store them in the knowledge-base. We conducted several experiments to test the capability of ASAF in recognizing the name entities and relationships using different approaches. Empirical evaluations of ASAF show promising performance results in terms of precision, recall, and [Formula: see text]-measure. The outcome of the presented framework could be utilized by semantic Web searching applications to retrieve precise answers to the end user smarter queries. An important feature of ASAF is that it could be ported to other domains with minimal extension. ASAF also contributes to the vision of the semantic Web in the target domains in Arabic Web sources.

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Baghdadi, Youcef. "Service-Oriented Software Engineering." International Journal of Systems and Service-Oriented Engineering 5, no. 2 (April 2015): 1–19. http://dx.doi.org/10.4018/ijssoe.2015040101.

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Method engineering techniques albeit proven effective for paradigms such as function, object and component, are pertinent to limited aspects of service orientation (SO). The comparison frameworks show that the produced methods neither conform to SO design principles nor to SOA, which is an issue. This paper proposes a framework to guide engineering methods for service-oriented software engineering. It describes a method by its aggregates and the relationships between elements such as Service Science (SS), SO, SOA, SOC, and Web. The paper also describes the guidance for method engineering. The framework consists of two layered categories of entities: (C1) conceptual foundation entities: SS, SO, and SOA, and (C2) realization infrastructure entities: SOC and Web. These entities request and provide services from/to each other. The framework comprehensively describes the SOSE environment, enforces the construct service with fundamental properties and principles, produces SOSE methods that address the challenges of software engineering, and benchmarks the existing SOSE methods.

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Fotsoh, Armel, Christian Sallaberry, and Annig Le Parc Lacayrelle. "Retrieval of Complex Named Entities on the Web: Proposals for Similarity Computation." International Journal of Information Technology and Computer Science 11, no. 11 (November 8, 2019): 1–14. http://dx.doi.org/10.5815/ijitcs.2019.11.01.

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Chu, Heting. "Taxonomy of inlinked Web entities: What does it imply for webometric research?" Library & Information Science Research 27, no. 1 (December 2005): 8–27. http://dx.doi.org/10.1016/j.lisr.2004.09.002.

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Nguyen, Truc-Vien T., and Tru H. Cao. "VN-KIM IE: Automatic Extraction of Vietnamese Named-Entities on the Web." New Generation Computing 25, no. 3 (May 2007): 277–92. http://dx.doi.org/10.1007/s00354-007-0018-4.

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Cao, Zhiying, Xinghao Qiao, Shuo Jiang, and Xiuguo Zhang. "An Efficient Knowledge-Graph-Based Web Service Recommendation Algorithm." Symmetry 11, no. 3 (March 18, 2019): 392. http://dx.doi.org/10.3390/sym11030392.

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Using semantic information can help to accurately find suitable services from a variety of available (different semantics) services, and the semantic information of Web services can be described in detail in a Web service knowledge graph. In this paper, a Web service recommendation algorithm based on knowledge graph representation learning (kg-WSR) is proposed. The algorithm embeds the entities and relationships of the knowledge graph into the low-dimensional vector space. By calculating the distance between service entities in low-dimensional space, the relationship information of services which is not considered in recommendation approaches using a collaborative filtering algorithm is incorporated into the recommendation algorithm to enhance the accurateness of the result. The experimental results show that this algorithm can not only effectively improve the accuracy rate, recall rate, and coverage rate of recommendation but also solve the cold start problem to some extent.

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Li, Yuan-Fang, Jeff Z. Pan, Shonali Krishnaswamy, Manfred Hauswirth, and Hai H. Nguyen. "The Ubiquitous Semantic Web." International Journal on Semantic Web and Information Systems 10, no. 4 (October 2014): 1–16. http://dx.doi.org/10.4018/ijswis.2014100101.

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The Semantic Web represents an evolution of the World Wide Web towards one of entities and their relationships, rather than pages and links. Such a progression makes it possible to represent, integrate, query and reason about structured online data. Recent years have witnessed tremendous growth of mobile computing, represented by the widespread adoption of smart phones and tablets. The versatility of such smart devices and the capabilities of semantic technologies form a great foundation for a ubiquitous Semantic Web that will contribute to further realising the true potential of both disciplines. In this paper, the authors argue for values provided by the ubiquitous Semantic Web using a mobile service discovery scenario. They also provide a brief overview of state-of-the-art research in this emerging area. Finally, the authors conclude with a summary of challenges and important research problems.

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JOERG, BRIGITTE, IVAN RUIZ-RUBE, MIGUEL-ANGEL SICILIA, JAN DVOŘÁK, KEITH JEFFERY, THORSTEN HOELLRIGL, HENRIK S. RASMUSSEN, ANDREAS ENGFER, THOMAS VESTDAM, and ELENA GARCIA BARRIOCANAL. "CONNECTING CLOSED WORLD RESEARCH INFORMATION SYSTEMS THROUGH THE LINKED OPEN DATA WEB." International Journal of Software Engineering and Knowledge Engineering 22, no. 03 (May 2012): 345–64. http://dx.doi.org/10.1142/s0218194012400074.

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Research Information Systems (RIS) play a critical role in the sharing of scientific information and provide researchers, professionals and decision makers with the required data for their activities. Existing RIS standards have proposed data models to represent the main entities for storage and exchange. These account for the needs of multiple stakeholders through a high flexibility based on a formal syntax and declared semantics, but for techno-historical reasons they assume the completeness of information within system boundaries. The distributed nature of research information across systems calls for a mechanism to link the local entities from the closed world of concrete RISs with other possibly underspecified entities exposed through other means, as for example, the Linked Open Data Web. By transformation of a relational model into an open graph model, differences between the two system paradigms are revealed. The main principles and techniques for exposing CERIF-driven relational data as linked data will be provided as a first step demonstrating effective RISs interconnection through the linked open data (LOD) Web.

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KARDAS, GEYLANI, ARDA GOKNIL, OGUZ DIKENELLI, and N. YASEMIN TOPALOGLU. "MODEL DRIVEN DEVELOPMENT OF SEMANTIC WEB ENABLED MULTI-AGENT SYSTEMS." International Journal of Cooperative Information Systems 18, no. 02 (June 2009): 261–308. http://dx.doi.org/10.1142/s0218843009002014.

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Semantic Web evolution brought a new vision into agent research. The interpretation of this second generation web will be realized by autonomous computational entities, called agents, to handle the semantic content on behalf of their human users. Surely, Semantic Web environment has specific architectural entities and a different semantic which must be considered to model a Multi-agent System (MAS) within this environment. Hence, in this study, we introduce a MAS development process which supports the Semantic Web environment. Our approach is based on Model Driven Development (MDD) which aims to change the focus of software development from code to models. We first define an architecture for Semantic Web enabled MASs and then provide a MAS metamodel which consists of the first class meta-entities derived from this architecture. We also define a model transformation process for MDD of such MASs. We present a complete transformation process in which the source and the target metamodels, entity mappings between models and the implementation of the transformation for two different real MAS frameworks by using a well-known model transformation language are all included. In addition to the model-to-model transformation, the implementation of the model-to-code transformation is given as the last step of the system development process. The evaluation of the proposed development process by considering its use within the scope of a real commercial software project is also discussed.

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Kuswinardi, Wiwin. "Pelatihan Pemanfaatan Web Pariwisata sebagai Pendukung Pelaksanaan Etourism bagi Entitas Pariwisata di Kabupaten Banyuwangi." Proceeding of Community Development 1 (January 30, 2018): 279. http://dx.doi.org/10.30874/comdev.2017.33.

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The concept of eTourism is a concept that implements information technology into the tourism sector. The key to eTourism is the integration of information that has the information collaboration capabilities and business processes of tourism entities making it possible to share information and business processes. Banyuwangi Regency that has begun to adopt the concept of eTourism is already time to apply the concept of information sharing by using web tourism managed by Disbudpar Banyuwangi as a source of tourism information. Tourism entities in Kabupaten Banyuwangi still have the opportunity to develop this potential and increase the potential for turnover and profit for tourism industry actors and increase local revenue through the tourism sector. The web utilization training provided has been able to provide the insights and skills of these entities, both from government and tourism industry actors.

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Ivanov, Dmitrii Nikolaevich. "The phenomenon of the Web State." Международные отношения, no. 3 (March 2022): 19–30. http://dx.doi.org/10.7256/2454-0641.2022.3.38625.

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The subject of the study is the fundamental possibility of State recognition (currently or in the foreseeable future) as a subject of international community law, existing only on the World Wide Web (the Decenturion - which is classified in the article as a web-state). The concept of the state itself is considered, the criteria for defining a certain entity as a state are distinguished, various types of states are distinguished based on their international status, the presence of territory and practical sovereignty over it. The features of the state in the generally accepted meaning of this word are distinguished, the features present in the web-state of the Decenturion and the features characteristic of traditional states, which the Decenturion does not have and cannot have, This topic has practically not been touched upon before in the scientific literature: the concepts of "digital state", "cyber state", "electronic government" are present in the title of many publications" and others, but the subject of these studies are not Internet entities that identify themselves as a "state", but various forms of presence on the World Wide Web of traditional states (websites of state structures, online services, etc.). Due to the lack of well-established terminology, the article attempts to streamline the terms used in relation to various entities that claim the status of a state, but have not received international recognition. It is concluded that it is possible in principle in the future for the international community to raise the issue of recognizing the web State as a subject of international law.

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Weikum, Gerhard. "Knowledge graphs 2021." Proceedings of the VLDB Endowment 14, no. 12 (July 2021): 3233–38. http://dx.doi.org/10.14778/3476311.3476393.

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Providing machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing vision and challenge for AI. Over the last 15 years, huge knowledge bases, also known as knowledge graphs, have been automatically constructed from web data, and have become a key asset for search engines and other use cases. Machine knowledge can be harnessed to semantically interpret texts in news, social media and web tables, contributing to question answering, natural language processing and data analytics. This position paper reviews these advances and discusses lessons learned. It highlights the role of "DB thinking" in building and maintaining high-quality knowledge bases from web contents. Moreover, the paper identifies open challenges and new research opportunities. In particular, extracting quantitative measures of entities (e.g., height of buildings or energy efficiency of cars), from text and web tables, presents an opportunity to further enhance the scope and value of knowledge bases.

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Hirsch, Peter Buell. "The Web unravels." Journal of Business Strategy 40, no. 5 (September 3, 2019): 54–58. http://dx.doi.org/10.1108/jbs-06-2019-0120.

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Purpose The purpose of this paper is to examine the impact of the splintering of the global internet into sovereign, government-controlled islands on the communications strategies and tactics of global corporations. Design/methodology/approach The approach taken was to review the various ways in which powerful authoritarian regimes such as Russia and China are controlling the Web to dissect the ways in which this could impact corporations. Findings The author believes that unless governments, civil entities and corporations collaborate to develop common standards for free speech and privacy, the Web as we know it today will cease to exist. Research limitations/implications The research is based on selected books and articles reviewed by the author and is not comprehensive. Practical implications Corporations will need to examine the impact of these developments on their own communications needs and strategies to develop the collaborations proposed. Social implications Without a universal global internet, the ability of citizens across the world to exchange ideas and develop strategies to tackle global problems will be severely curtailed. Originality/value The author does not believe that the splintering of the internet has been considered from the perspective of the global corporation.

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Lamurias, Andre, João D. Ferreira, and Francisco M. Couto. "Identifying interactions between chemical entities in biomedical text." Journal of Integrative Bioinformatics 11, no. 3 (December 1, 2014): 1–16. http://dx.doi.org/10.1515/jib-2014-247.

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Summary Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, “Identifying Interactions between Chemical Entities” (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to stateof- the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.

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Kadaba, Rajiv, Suratna Budalakoti, David DeAngelis, and K. Suzanne Barber. "Modeling Virtual Footprints." International Journal of Agent Technologies and Systems 3, no. 2 (April 2011): 1–17. http://dx.doi.org/10.4018/jats.2011040101.

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Entities interacting on the web establish their identity by creating virtual personas. These entities, or agents, can be human users or software-based. This research models identity using the Entity-Persona Model, a semantically annotated social network inferred from the persistent traces of interaction between personas on the web. A Persona Mapping Algorithm is proposed which compares the local views of personas in their social network referred to as their Virtual Signatures, for structural and semantic similarity. The semantics of the Entity-Persona Model are modeled by a vector space model of the text associated with the personas in the network, which allows comparison of their Virtual Signatures. This enables all the publicly accessible personas of an entity to be identified on the scale of the web. This research enables an agent to identify a single entity using multiple personas on different networks, provided that multiple personas exhibit characteristic behavior. The agent is able to increase the trustworthiness of on-line interactions by establishing the identity of entities operating under multiple personas. Consequently, reputation measures based on on-line interactions with multiple personas can be aggregated and resolved to the true singular identity.

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López Martínez, Javier. "Free software for digitalization and management of electronic documents at official entities." Sistemas y Telemática 15, no. 40 (April 5, 2017): 69–87. http://dx.doi.org/10.18046/syt.v15i40.2392.

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Taking into account the current regulations in Colombia about document management and best practices, a technological solution for digitization and document management in public sector entities was designed, following the Research Applied method. The solution includes the integration of two Web systems focused on free software. The first one, called FuidXel, is a development in PHP language, original of the present project, that includes a tool next to the client for digitization, and a Web application, next to the server, for the conformation of the document, that consists on libraries of tools for the treatment of images and PDF files. The second system is an enterprise content manager for managing electronic documents, called Alfresco. FuidXel integrates with Alfresco through CMIS protocol for the sending of PDF documents, made up of the product images of the digitization and management, information and traceability metadata.

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Evans, A. J., and T. Waters. "Mapping vernacular geography: web-based GIS tools for capturing 'fuzzy' or 'vague' entities." International Journal of Technology, Policy and Management 7, no. 2 (2007): 134. http://dx.doi.org/10.1504/ijtpm.2007.014547.

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Journal articles on the topic 'Entities on the Web'

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