{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:39:11Z","timestamp":1761007151234,"version":"build-2065373602"},"reference-count":10,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2015,4,24]],"date-time":"2015-04-24T00:00:00Z","timestamp":1429833600000},"content-version":"vor","delay-in-days":478,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc of Assoc for Info"],"published-print":{"date-parts":[[2014,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>While classical bag\u2010of\u2010word (BoG) approaches represent text content in the word level, recent studies show that knowledge\u2010based concept indexation is a promising approach to further enhance the text search and mining performance. In this study, we propose a new knowledge indexation\/extraction method, Explicit Semantic Path Mining (ESPM), for knowledge\u2010base text mining. It has roots in a concept\u2010based vector constructing method, Explicit Semantic Analysis (ESA), which has shown success in text mining tasks. For this new method, given an input piece of text, ESPM can efficiently identify the independent and optimized semantic path(s) on a concept map, which is, in this study, the Wikipedia category tree. Unlike earlier studies focusing on BoG based vector space, ESPM is a semantic path mining algorithm, which generates the top down semantic categories of a given text by leveraging the rich link information between Wikipedia categories and articles. Preliminary experiment based on ODP data shows ESPM delivers high quality independent semantic paths from both precision and ranking viewpoints.<\/jats:p>","DOI":"10.1002\/meet.2014.14505101160","type":"journal-article","created":{"date-parts":[[2015,4,24]],"date-time":"2015-04-24T17:19:02Z","timestamp":1429895942000},"page":"1-4","source":"Crossref","is-referenced-by-count":0,"title":["Explicit semantic path mining via wikipedia knowledge tree"],"prefix":"10.1002","volume":"51","author":[{"given":"Tian","family":"Xia","sequence":"first","affiliation":[{"name":"School of Information Resource Management Renmin University of China"}]},{"given":"Miao","family":"Chen","sequence":"additional","affiliation":[{"name":"Data To Insight Center Indiana University  Bloomington"}]},{"given":"Xiaozhong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Information and Library Science Indiana University  Bloomington"}]}],"member":"311","published-online":{"date-parts":[[2015,4,24]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"crossref","unstructured":"Anderka M. &Stein B.(2009 July).The ESA retrieval model revisited. In Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retriev\u2010al (pp.670\u2013671).ACM.","DOI":"10.1145\/1571941.1572070"},{"issue":"32","key":"e_1_2_7_3_1","first-page":"175","article-title":"Knowledge\u2010based recommender systems","volume":"69","author":"Burke R.","year":"2000","journal-title":"Encyclopedia of library and information systems"},{"key":"e_1_2_7_4_1","doi-asserted-by":"crossref","unstructured":"Chakrabarti D. &Mehta R.(2010).The paths more taken: matching DOM trees to search logs for accurate webpage clustering. In Proceedings of the 19th international conference on World wide web (pp.211\u2013220).ACM.","DOI":"10.1145\/1772690.1772713"},{"key":"e_1_2_7_5_1","first-page":"2297","article-title":"Harnessing the Expertise of 70, 000 Human Editors: Knowledge\u2010Based Feature Generation for Text Categorization","volume":"8","author":"Gabrilovich E.","year":"2007","journal-title":"Journal of Machine Learning Re\u2010search"},{"key":"e_1_2_7_6_1","first-page":"1301","article-title":"Overcoming the brittleness bottleneck using Wikipedia: Enhancing text categorization with encyclopedic knowledge","volume":"6","author":"Gabrilovich E.","year":"2006","journal-title":"AAAI"},{"key":"e_1_2_7_7_1","unstructured":"Hotho A. Staab S. &Stumme G.(2003a).Ontologies improve text document clustering. Paper presented at the Third IEEE International Conference on Data Mining (ICDM'03)."},{"key":"e_1_2_7_8_1","unstructured":"Liu X. Yu Y. Guo C. SunY. &GaoL.(2014).A Comparative Study of Academic impact and Wikipedia Ranking ACM\/IEEE Joint Conference on Digital Libraries (JCDL)."},{"key":"e_1_2_7_9_1","first-page":"157","volume-title":"Symbolic and Numeric Algorithms for Scientific Computing, 2007","author":"Minier Z.","year":"2007"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16020-2_22"},{"key":"e_1_2_7_11_1","doi-asserted-by":"crossref","unstructured":"Ramage D. Hall D. Nallapati R.&Manning C.D.(2009).Labeled LDA: A supervised topic model for credit attribution in multi\u2010labeled corpora. In EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.","DOI":"10.3115\/1699510.1699543"}],"container-title":["Proceedings of the American Society for Information Science and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fmeet.2014.14505101160","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fmeet.2014.14505101160","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/asistdl.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/meet.2014.14505101160","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T12:03:27Z","timestamp":1760961807000},"score":1,"resource":{"primary":{"URL":"https:\/\/asistdl.onlinelibrary.wiley.com\/doi\/10.1002\/meet.2014.14505101160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,1]]},"references-count":10,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,1]]}},"alternative-id":["10.1002\/meet.2014.14505101160"],"URL":"https:\/\/doi.org\/10.1002\/meet.2014.14505101160","archive":["Portico"],"relation":{},"ISSN":["0044-7870","1550-8390"],"issn-type":[{"type":"print","value":"0044-7870"},{"type":"electronic","value":"1550-8390"}],"subject":[],"published":{"date-parts":[[2014,1]]}}}