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7 . [1] Chen J., Chen H. A Structured Informaton Extracton Algorthm for Scentfc Papers based on Feature Rules Learnng // Journal of Software, Vol. 8, No. 1, January P [2] DeRose P., Shen W., Chen F., Doan AH, Ramakrshnan R. Buldng Structured Web Communty Portals: A Top-Down, Compostonal, and Incremental Approach // VLDB 07, September 23-28, 2007, Venna, Austra. P [3] Ferrara E., De Meo P., Fumara G., Baumgartner R. Web Data Extracton, Applcatons and Technques: A Survey // Preprnt submtted to Knowledge-based systems. June 5, p. [4] Guarno N. Formal Ontology n Informaton Systems // Formal Ontology n Informaton Systems. Proceedngs of FOIS'98, Trento, Italy, June 6 8, 1998 / Ed. N. Guarno. Amsterdam: IOS Press, P [5] Hllmann D. Usng Dubln Core, [6] Labský M., Svátek V., Nekvasl M., Rak D. The Ex Project: Web Informaton Extracton Usng Extracton Ontologes // Knowledge Dscovery Enhanced wth Semantc and Socal Informaton. Studes n Computatonal Intellgence. Berln: Sprnger-Verlag, vol. 220, p [7] Saggon H., Funk A., Maynard D., Bontcheva K. Ontology-based Informaton Extracton for Busness Intellgence // Proceedngs of the 6th nternatonal The semantc web (ISWC'07) and 2nd Asan conference on Asan semantc web conference (ASWC'07). Berln, Hedelberg: Sprnger-Verlag, P [8] Stenback J., Le Hégaret P., Le Hors A. Document Object Model (DOM) Level 2 HTML Specfcaton // W3C Recommendaton, HTML / [9] Zha Y., Lu B. Extractng Web Data Usng Instance-Based Learnng // Proceedngs of 6th Internatonal Conference on Web Informaton Systems Engneerng (WISE-05), P [10]..,..,..,..,..,.. - //. : , [11].. - // , C [12]..,..,..,.. - // XV RCDL :, C [13]..,..,.. // - «,» ( 4): I, C An Automatzaton of Collecton of Informaton about Scentfc Actvty for Thematc Intellgent Scentfc Internet Resources Yury A. Zagorulko, Irna R. Akhmadeeva, Alexey S. Sery The paper consders the problems of nformaton collecton and extracton for thematc ntellgent scentfc nternet resources provdng the systematzaton and ntegraton of scentfc knowledge, nformaton resources and methods of ntellgent nformaton processng related to certan area of knowledge, as well as the content-based access to them. The approach to automatzaton of collecton of nformaton about scentfc actvty n the gven knowledge area combnng metasearch and knowledge extracton methods based on ontology and thesaurus s proposed. In accordance of ths approach for every type of enttes (ontology class) the specfc methods of nformaton collecton and extracton adjustable to knowledge area and types of nformaton resources s developed. Each of these methods ncludes a set of patterns. In these patterns, for every knd of extracted nformaton, markers defnng ts poston are gven as well as the engnes mplementng the algorthm of the analyss of the correspondng fragments of Web pages and extracton of the requred nformaton from them. These patterns are generated on the bass of the ontology. To mprove the recall of nformaton extracton, the patterns use alternatve terms n dfferent languages from thesaurus (synonyms and hyponyms) to descrbe the markers. 68