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Статті в журналах з теми "Entities on the Web"
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.
Повний текст джерелаHuang, 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.
Повний текст джерелаThakare, 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.
Повний текст джерелаYin 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.
Повний текст джерелаJang, 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.
Повний текст джерелаBarbosa, 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.
Повний текст джерелаDai, 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.
Повний текст джерелаSung, 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.
Повний текст джерелаPresutti, 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.
Повний текст джерелаKöpcke, 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.
Повний текст джерелаДисертації з теми "Entities on the Web"
Iofciu, Tereza [Verfasser]. "Users and entities on the web / Tereza Iofciu." Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2013. http://d-nb.info/1035391759/34.
Повний текст джерелаUrbansky, David. "Automatic Extraction and Assessment of Entities from the Web." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-97469.
Повний текст джерелаAlsarem, Mazen. "Semantic snippets via query-biased ranking of linked data entities." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI044/document.
Повний текст джерелаIn this thesis, we introduce a new interactive artifact for the SERP: the "Semantic Snippet". Semantic Snippets rely on the coexistence of the two webs to facilitate the transfer of knowledge to the user thanks to a semantic contextualization of the user's information need. It makes apparent the relationships between the information need and the most relevant entities present in the web page
Demartini, Gianluca [Verfasser]. "From people to entities : typed search in the enterprise and the web / Gianluca Demartini." Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2011. http://d-nb.info/1013472055/34.
Повний текст джерелаGunaratna, Kalpa. "Semantics-based Summarization of Entities in Knowledge Graphs." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1496124815009777.
Повний текст джерелаNakashole, Ndapandula T. [Verfasser], and Gerhard [Akademischer Betreuer] Weikum. "Automatic extraction of facts, relations, and entities for web-scale knowledge base population / Ndapandula T. Nakashole. Betreuer: Gerhard Weikum." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2013. http://d-nb.info/1052779654/34.
Повний текст джерелаGUDIVADA, RANGA CHANDRA. "DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1195161740.
Повний текст джерелаFotsoh, Tawaofaing Armel. "Recherche d’entités nommées complexes sur le web : propositions pour l’extraction et pour le calcul de similarité." Thesis, Pau, 2018. http://www.theses.fr/2018PAUU3003/document.
Повний текст джерелаRecent developments in information technologies have made the web an important data source. However, the web content is very unstructured. Therefore, it is a difficult task to automatically process this web content in order to extract relevant information. This is a reason why research work related to Information Extraction (IE) on the web are growing very quickly. Similarly, another very explored research area is the querying of information extracted on the web to answer an information need. This other research area is known as Information Retrieval (IR). Our research work is at the crossroads of both areas. The main goal of our work is to develop strategies and techniques for crawling the web in order to extract complex Named Entities (NEs) (NEs with several properties that may be text or other NEs). We then propose to index them and to query them in order to answer information needs. This work was carried out within the T2I team of the LIUPPA laboratory, in collaboration with Cogniteev, a company which core business is focused on the analysis of web content. The issues we had to deal with were the extraction of complex NEs on the web and the development of IR services supplied by the extracted data. Our first contribution is related to complex NEs extraction from text content. For this contribution, we take into consideration several problems, in particular the noisy context characterizing some properties (the web page describing an event for example, may contain more than one dates: the event’s date and the date of ticket’s sales opening). For this particular problem, we introduce a block detection module that focuses property's extraction on relevant text blocks. Our experiments show an improvement of system’s performances. We also focused on address extraction where the main issue arises from the fact that there is not a standard way for writing addresses in general and on the web in particular. We therefore propose a pattern-based approach which uses some lexicons for extracting addresses from text, regardless of proprietary resources.Our second contribution deals with similarity computation between complex NEs. In the state of the art, this similarity computation is generally performed in two steps: (i) first, similarities between properties are calculated; (ii) then the obtained similarities are aggregated to compute the overall similarity. Our main proposals focuses on the second step. We propose three techniques for aggregating property’s similarities. The first two are based on the weighted sum of these property’s similarities (simple linear combination and logistic regression). The third technique however, uses decision trees for the aggregation. Finally, we also propose a last approach based on clustering and Salton vector model. This last approach evaluates the similarity at the complex NE level without computing property’s similarities. We also propose a similarity computation function between spatial EN, one represented by a point and the other by a polygon. This completes those of the state of the art
Urbansky, David [Verfasser], Alexander [Akademischer Betreuer] Schill, James [Akademischer Betreuer] Thom, and Michael [Akademischer Betreuer] Schroeder. "Automatic Extraction and Assessment of Entities from the Web / David Urbansky. Gutachter: Alexander Schill ; James Thom ; Michael Schroeder. Betreuer: Alexander Schill ; James Thom." Dresden : Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://d-nb.info/1068148233/34.
Повний текст джерелаWatanabe, Willian Massami. "Auxílio à leitura de textos em português facilitado: questões de acessibilidade." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-22092010-164526/.
Повний текст джерелаThe large capacity of Web for providing information leads to multiple possibilities and opportunities for users. The development of high performance networks and ubiquitous devices allow users to retrieve content from any location and in different scenarios or situations they might face in their lives. Unfortunately the possibilities offered by the Web are not necessarily currently available to all. Individuals who do not have completely compliant software or hardware that are able to deal with the latest technologies, or have some kind of physical or cognitive disability, find it difficult to interact with web pages, depending on the page structure and the ways in which the content is made available. When specifically considering the cognitive disabilities, users classified as functionally illiterate face severe difficulties accessing web content. The heavy use of texts on interfaces design creates an accessibility barrier to those who cannot read fluently in their mother tongue due to both text length and linguistic complexity. In this context, this work aims at developing an assistive technologies that assists functionally illiterate users during their reading and understanding of websites textual content. These assistive technologies make use of natural language processing (NLP) techniques that maximize reading comprehension for users. The natural language techniques that this work uses are: syntactic simplification, automatic summarization, lexical elaboration and named entities recognition. The techniques are used with the goal of automatically adapting textual content available on the Web for users with low literacy levels. This work describes the accessibility characteristics incorporated into both resultant applications (Facilita and Educational Facilita) that focus on low literacy users limitations towards computer usage and experience. This work contributed with the identification of accessibility requirements for low-literacy users, elaboration of an accessibility model for automatizing WCAG conformance and development of accessible solutions in the user agents layer of web applications
Книги з теми "Entities on the Web"
Inc, ebrary, ed. WCF 4.0 multi-tier services development with LINQ to entities: Build SOA applications on the Microsoft platform with this hands-on guide updated for VS2010. Birmingham [England]: Packt Pub., 2010.
Знайти повний текст джерелаSekine, Satoshi, and Elisabete Ranchhod, eds. Named Entities. Amsterdam: John Benjamins Publishing Company, 2009. http://dx.doi.org/10.1075/bct.19.
Повний текст джерелаCowling, Sam. Abstract Entities. 1 [edition]. | New York : Routledge, 2017. | Series: New problems: Routledge, 2017. http://dx.doi.org/10.4324/9781315266619.
Повний текст джерелаAbstract entities. Basingstoke: Macmillan, 1992.
Знайти повний текст джерелаTeichmann, Roger. Abstract Entities. London: Palgrave Macmillan UK, 1992. http://dx.doi.org/10.1007/978-1-349-21863-9.
Повний текст джерелаAbstract entities. New York: St. Martin's Press, 1992.
Знайти повний текст джерелаBurgdoerfer, Jerry J. Illinois business entities. Newark, N.J: LexisNexis Matthew Bender, 2005.
Знайти повний текст джерелаUnincorporated business entities. Cincinnati: Anderson Pub. Co., 1996.
Знайти повний текст джерелаUnincorporated business entities. 3rd ed. Newark, NJ: LexisNexis, 2004.
Знайти повний текст джерелаM, Lipshaw Jeffrey, ed. Unincorporated business entities. 4th ed. Newark, NJ: LexisNexis, 2009.
Знайти повний текст джерелаЧастини книг з теми "Entities on the Web"
Gangemi, Aldo, Andrea Giovanni Nuzzolese, Valentina Presutti, Francesco Draicchio, Alberto Musetti, and Paolo Ciancarini. "Automatic Typing of DBpedia Entities." In The Semantic Web – ISWC 2012, 65–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35176-1_5.
Повний текст джерелаSigletos, Georgios, Georgios Paliouras, Constantine D. Spyropoulos, and Michalis Hatzopoulos. "Mining Web Sites Using Wrapper Induction, Named Entities, and Post-processing." In Web Mining: From Web to Semantic Web, 97–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30123-3_6.
Повний текст джерелаYou, Yongjian, Shaohua Zhang, Jiong Lou, Xinsong Zhang, and Weijia Jia. "Neural Typing Entities in Chinese-Pedia." In Web and Big Data, 385–99. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96890-2_32.
Повний текст джерелаChristophides, Vassilis, Vasilis Efthymiou, and Kostas Stefanidis. "Matching and Resolving Entities." In Entity Resolution in the Web of Data, 17–38. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-031-79468-1_2.
Повний текст джерелаNguyen, Tu Ngoc, Nattiya Kanhabua, and Wolfgang Nejdl. "Multiple Models for Recommending Temporal Aspects of Entities." In The Semantic Web, 462–80. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93417-4_30.
Повний текст джерелаKozareva, Zornitsa, Joaquim Silva, Pablo Gamallo, and Gabriel Lopes. "Cluster Analysis of Named Entities." In Intelligent Information Processing and Web Mining, 429–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39985-8_47.
Повний текст джерелаBarrière, Caroline. "Searching for Named Entities." In Natural Language Understanding in a Semantic Web Context, 23–38. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41337-2_3.
Повний текст джерелаThalhammer, Andreas, and Achim Rettinger. "PageRank on Wikipedia: Towards General Importance Scores for Entities." In The Semantic Web, 227–40. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47602-5_41.
Повний текст джерелаWang, Chengyu, Rong Zhang, Xiaofeng He, Guomin Zhou, and Aoying Zhou. "NERank: Bringing Order to Named Entities from Texts." In Web Technologies and Applications, 15–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45814-4_2.
Повний текст джерелаBarrière, Caroline. "Entities, Labels, and Surface Forms." In Natural Language Understanding in a Semantic Web Context, 9–22. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41337-2_2.
Повний текст джерелаТези доповідей конференцій з теми "Entities on the Web"
Demartini, Gianluca, Claudiu S. Firan, Mihai Georgescu, Tereza Iofciu, Ralf Krestel, and Wolfgang Nejdl. "An Architecture for Finding Entities on the Web." In 2009 Latin American Web Congress (LA-WEB). IEEE, 2009. http://dx.doi.org/10.1109/la-web.2009.14.
Повний текст джерелаSpaniol, Marc, and Gerhard Weikum. "Tracking entities in web archives." In the 21st international conference companion. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2187980.2188030.
Повний текст джерелаThompson, Henry S., Jonathan Rees, and Jeni Tennison. "URIs in data: for entities, or for descriptions of entities—A critical analysis." In the 5th Annual ACM Web Science Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2464464.2532514.
Повний текст джерелаDemartini, Gianluca, Claudiu S. Firan, Tereza Iofciu, Ralf Krestel, and Wolfgang Nejdl. "A Model for Ranking Entities and Its Application to Wikipedia." In 2008 Latin American Web Conference (LA-WEB). IEEE, 2008. http://dx.doi.org/10.1109/la-web.2008.8.
Повний текст джерелаGamon, Michael, Tae Yano, Xinying Song, Johnson Apacible, and Patrick Pantel. "Identifying salient entities in web pages." In the 22nd ACM international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2505515.2505602.
Повний текст джерелаJain, Alpa, and Patrick Pantel. "Identifying comparable entities on the web." In Proceeding of the 18th ACM conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1645953.1646198.
Повний текст джерелаYu, Wei, Junpeng Chen, and Guoying Yu. "Discovering Entities Relationships on the Web." In 2008 Second IEEE International Conference on Semantic Computing (ICSC). IEEE, 2008. http://dx.doi.org/10.1109/icsc.2008.16.
Повний текст джерелаIdeh, Azari, and Koohpeyma Fateme. "Disambiguating named entities by semantic web." In 3rd International Conference on Computer Science and Service System. Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/csss-14.2014.173.
Повний текст джерелаHo, Vinh Thinh, Koninika Pal, Niko Kleer, Klaus Berberich, and Gerhard Weikum. "Entities with Quantities." In WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3336191.3371860.
Повний текст джерелаHeist, Nicolas, and Heiko Paulheim. "Information Extraction From Co-Occurring Similar Entities." In WWW '21: The Web Conference 2021. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3442381.3449836.
Повний текст джерелаЗвіти організацій з теми "Entities on the Web"
Lewis, Dustin, ed. International Counterterrorism Efforts: An Initial Mapping. Harvard Law School Program on International Law and Armed Conflict, February 2015. http://dx.doi.org/10.54813/ktkl6017.
Повний текст джерелаLutz, Carsten. Adding Numbers to the SHIQ Description Logic - First Results. Aachen University of Technology, 2001. http://dx.doi.org/10.25368/2022.117.
Повний текст джерелаDahl, Deborah A. Determiners, Entities, and Contexts. Fort Belvoir, VA: Defense Technical Information Center, October 1986. http://dx.doi.org/10.21236/ada458702.
Повний текст джерелаDecleir, Cyril, Mohand-Saïd Hacid, and Jacques Kouloumdjian. A Database Approach for Modeling and Querying Video Data. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.90.
Повний текст джерелаMcCall, Jamie, Nora Anzawi, Miles Zeller, and James Onorevole. Growth, Equity, and Individual Welfare: A Theoretical Framework for “Moving the Needle” on CDFI Impact Evaluation. Carolina Small Business Development Fund and AltCap, January 2023. http://dx.doi.org/10.46712/evaluation.frameworks.
Повний текст джерелаQin, Hua, Yanu Prasetyo, Christine Sanders, Elizabeth Prentice, and Muh Syukron. Perceptions and behaviors in response to the novel coronavirus disease 2019 (COVID-19) : reports on major survey findings. University of Missouri, Division of Applied Social Sciences, 2020. http://dx.doi.org/10.32469/10355/79261.
Повний текст джерелаSalz, R. Entities Involved in the IETF Standards Process. RFC Editor, June 2022. http://dx.doi.org/10.17487/rfc9281.
Повний текст джерелаAldrich, Susan. Web Services Backplane: Infrastructure for Web Services. Boston, MA: Patricia Seybold Group, January 2003. http://dx.doi.org/10.1571/la1-2-03cc.
Повний текст джерелаNottingham, M. Web Linking. RFC Editor, October 2010. http://dx.doi.org/10.17487/rfc5988.
Повний текст джерелаKramer, Mitch. Nina Web. Boston, MA: Patricia Seybold Group, January 2014. http://dx.doi.org/10.1571/pr01-30-14cc.
Повний текст джерела