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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track Zhai, Haijun; Cheng, Xueqi; Guo, Jiafeng... In: DTIC (2009) BASE Show details 2 Relevance Feedback based on Constrained Clustering: FDU at TREC 09 Wang, Bingqing; Huang, Xuanjing In: DTIC (2009) BASE Show details 3 ICTNET at Web Track 2009 Diversity task Bi, Wenjing; Yu, Xiaoming; Liu, Yue... In: DTIC (2009) BASE Show details 4 BIT at TREC 2009 Faceted Blog Distillation Task Jiang, Peng; Yang, Qing; Zhang, Chunxia... In: DTIC (2009) BASE Show details 5 Entity Retrieval by Hierarchical Relevance Model, Exploiting the Structure of Tables and Learning Homepage Classifiers Fang, Yi; Si, Luo; Yu, Zhengtao... In: DTIC (2009) BASE Show details 6 PRIS at 2009 Relevance Feedback track: Experiments in Language Model for Relevance Feedback Li, Si; Li, Xinsheng; Zhang, Hao... In: DTIC (2009) BASE Show details 7 A Study of Faceted Blog Distillation -- PRIS at TREC 2009 Blog Track Li, Si; Gao, Huiji; Gao, Juiji... In: DTIC (2009) BASE Show details 8 Microsoft Research at TREC 2009. Web and Relevance Feedback Tracks Craswell, Nick; Fetterly, Dennis; Najork, Marc... In: DTIC (2009) BASE Show details 9 Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task Lex, Elisabeth; Granitzer, Michael; Juffinger, Andreas In: DTIC (2009) Abstract: In this paper, we outline our experiments carried out at the TREC 2009 Blog Distillation Task. Our system is based on a plain text index extracted from the XML feeds of the TREC Blogs08 dataset. This index was used to retrieve candidate blogs for the given topics. The resulting blogs were classified using a Support Vector Machine that was trained on a manually labelled subset of the TREC Blogs08 dataset. Our experiments included three runs on different features: firstly on nouns, secondly on stylometric properties, and thirdly on punctuation statistics. The facet identification based on our approach was successful, although a significant number of candidate blogs were not retrieved at all. ; Presented at the Text REtrieval Conference (TREC 2009, 18th) held in Gaithersburg, Maryland on 17-20 November 2009. Published in the Proceedings of the Text REtrieval Conference (TREC 2009, 18th), 2009. The conference was co-sponsored by the National Institute of Standards and Technology (NIST), the Defense Advanced Research Projects Agency (DARPA), and the Advanced Research and Development Activity (ARDA). Keyword: *BLOGS(INTERNET); *INFORMATION RETRIEVAL; *INFORMATION SCIENCES; *INTERNET; *IR(INFORMATION RETRIEVAL); *SOCIAL COMMUNICATION; AUSTRIA; Computer Programming and Software; DISTILLATION; Equipment and Methods; FOREIGN REPORTS; Information Science; Linguistics; RELEVANCE(INFORMATION SCIENCES); REPRINTS; STYLOMETRICS; SVM(SUPPORT VECTOR MACHINES); SYMPOSIA; Test Facilities; WORDS(LANGUAGE) URL: http://www.dtic.mil/docs/citations/ADA517854 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA517854 BASE Hide details

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