{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:08:44Z","timestamp":1754158124283,"version":"3.41.2"},"reference-count":25,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2009,8,7]],"date-time":"2009-08-07T00:00:00Z","timestamp":1249603200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,8,7]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to identify distinguishing term characteristics from among the information of term appearance situations (<jats:italic>tas<\/jats:italic>) residing in the relevant\/irrelevant documents retrieved for use. Terms with specific characteristics could be used in the distinguishing of user profiles, documents, pages or concepts to assist in information retrieval.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>First, a method to apply the potential term characteristics in the distinguishing of user profiles in the information retrieval environment is designed. Then, an information retrieval system is developed to demonstrate the realisation and sustain the study of the method. Formal tests are conducted to examine the distinguishing capability of the potential term characteristics proposed in the method.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The results of the tests show that the potential term characteristics proposed in this study are successfully applied in the distinguishing of user profiles in the information retrieval environment.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>Identification of distinguishing term characteristics would expand the ground for the IR community in the design of feature\u2010extraction algorithms or systems that try to cull information from structured or unstructured documents.<\/jats:p><\/jats:sec>","DOI":"10.1108\/14684520910985701","type":"journal-article","created":{"date-parts":[[2009,10,5]],"date-time":"2009-10-05T10:28:03Z","timestamp":1254738483000},"page":"745-760","source":"Crossref","is-referenced-by-count":1,"title":["The identification of distinguishing term characteristics from relevance feedback"],"prefix":"10.1108","volume":"33","author":[{"given":"Shihchieh","family":"Chou","sequence":"first","affiliation":[]},{"given":"Weiping","family":"Chang","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022031219421310900_b1","unstructured":"Azimi\u2010Sadjadi, M., Salazar, J., Srinivasan, S. and Sheedvash, S. (2004), \u201cAn adaptable connectionist text retrieval system with relevance feedback\u201d, Proceedings of IEEE International Joint Conference on Neural Networks, Budapest, July 2004, pp. 309\u2010314."},{"key":"key2022031219421310900_b2","doi-asserted-by":"crossref","unstructured":"Balabanovic, M. (1997), \u201cAn adaptive web page recommendation service\u201d, Proceedings of the First International Conference on Autonomous Agents, New York, February, pp. 378\u2010385.","DOI":"10.1145\/267658.267744"},{"key":"key2022031219421310900_b3","doi-asserted-by":"crossref","unstructured":"Buckley, C. and Salton, G. (1995), \u201cOptimization of relevance feedback weights\u201d, Proceedings of the Eighteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, July, pp. 351\u2010357.","DOI":"10.1145\/215206.215383"},{"key":"key2022031219421310900_b4","doi-asserted-by":"crossref","unstructured":"Choi, J., Kim, M. and Raghavan, V. (2006), \u201cAdaptive relevance feedback method of extended Boolean model using hierarchical clustering techniques\u201d, Information Processing and Management, Vol. 42 No. 2, pp. 331\u201049.","DOI":"10.1016\/j.ipm.2005.05.009"},{"key":"key2022031219421310900_b5","unstructured":"Desjardins, G. and Godin, R. (2000), \u201cCombining relevance feedback and genetic algorithms in an internet information filtering engine\u201d, Proceedings of the RIAO2000 Conference, Paris, April, pp. 1676\u20101685."},{"key":"key2022031219421310900_b6","doi-asserted-by":"crossref","unstructured":"Edmundson, H.P. (1969), \u201cNew methods in automatic extracting\u201d, Journal of Association for Computing Machinery, Vol. 16 No. 2, pp. 264\u201085.","DOI":"10.1145\/321510.321519"},{"key":"key2022031219421310900_b7","unstructured":"Ekkelenkamp, R., Kraaij, W. and Leeuwen, D. (1998), \u201cTNO TREC7 site report: SDR and filtering\u201d, Proceedings of the Seventh Text Retrieval Conference, Gaithersburg, MD, November, pp. 455\u2010462."},{"key":"key2022031219421310900_b8","doi-asserted-by":"crossref","unstructured":"Fresno, V. and Ribeiro, A. (2004), \u201cAn analytical approach to concept extraction in HTML environment\u201d, Journal of Intelligent Information Systems, Vol. 22 No. 3, pp. 215\u201035.","DOI":"10.1023\/B:JIIS.0000019277.82436.17"},{"key":"key2022031219421310900_b9","unstructured":"Ide, E. (1971), \u201cNew experiments in relevance feedback\u201d, in Salton, G. (Ed.), The SMART Retrieval System: Experiments in Automatic Document Processing, Prentice\u2010Hall, Upper Saddle River, NJ, pp. 337\u201054."},{"key":"key2022031219421310900_b10","unstructured":"Ives, Z. (2008), \u201cGoogle, web crawling, and distributed synchronization\u201d, available at: www.seas.upenn.edu\/ \u223c\u2009zives\/cis555\/slides\/I\u2010Crawlers\u2010Sync.ppt#1 (accessed 6 October 2008)."},{"key":"key2022031219421310900_b11","doi-asserted-by":"crossref","unstructured":"Justino, E., Bortolozzi, F. and Sabourin, R. (2005), \u201cA comparison of SVM and HMM classifiers in the off\u2010line signature verification\u201d, Pattern Recognition Letters, Vol. 26 No. 9, pp. 1377\u201085.","DOI":"10.1016\/j.patrec.2004.11.015"},{"key":"key2022031219421310900_b12","unstructured":"Kim, B., Kim, J. and Kim, J. (2001), \u201cQuery term expansion and re\u2010weighting using term co\u2010occurrence similarity and fuzzy inference\u201d, Proceedings of IFSA World Congress and the 20th NAFIPS International Conference, Vancouver, July, pp. 715\u2010720."},{"key":"key2022031219421310900_b13","doi-asserted-by":"crossref","unstructured":"Koster, C. and Beney, J. (2007), \u201cOn the importance of parameter tuning in text categorization\u201d, Lecture Notes in Computer Science, No. 4378, pp. 270\u201083.","DOI":"10.1007\/978-3-540-70881-0_24"},{"key":"key2022031219421310900_b14","doi-asserted-by":"crossref","unstructured":"Moschitti, A. (2003), \u201cA study on optimal parameter tuning for Rocchio text classifier\u201d, Proceedings of the 25th European Conference on Information Retrieval Research, Pisa, April, pp. 420\u2010435.","DOI":"10.1007\/3-540-36618-0_30"},{"key":"key2022031219421310900_b15","doi-asserted-by":"crossref","unstructured":"Nick, Z. and Themis, P. (2001), \u201cWeb search using a genetic algorithm\u201d, IEEE Internet Computing, Vol. 5 No. 2, pp. 18\u201026.","DOI":"10.1109\/4236.914644"},{"key":"key2022031219421310900_b16","doi-asserted-by":"crossref","unstructured":"Okabe, M. and Yamada, S. (2005), \u201cLearning filtering rulesets for ranking refinement in relevance feedback\u201d, Knowledge\u2010based Systems, Vol. 18 Nos 2\u20103, pp. 117\u201024.","DOI":"10.1016\/j.knosys.2004.04.011"},{"key":"key2022031219421310900_b17","doi-asserted-by":"crossref","unstructured":"Ou, S., Khoo, C. and Goh, D. (2008), \u201cDesign and development of a concept\u2010based multi\u2010document summarization system for research abstracts\u201d, Journal of Information Science, Vol. 34 No. 3, pp. 308\u201026.","DOI":"10.1177\/0165551507084630"},{"key":"key2022031219421310900_b18","unstructured":"Rocchio, J. (1966), \u201cDocument retrieval systems \u2013 optimization and evaluation\u201d, Unpublished doctoral dissertation, Harvard University, Cambridge, MA."},{"key":"key2022031219421310900_b19","doi-asserted-by":"crossref","unstructured":"Rumpler, B. (2001), \u201cA study of the impact of the user profile in documentary systems\u201d, Online Information Review, Vol. 25 No. 6, pp. 359\u201064.","DOI":"10.1108\/14684520110412894"},{"key":"key2022031219421310900_b20","doi-asserted-by":"crossref","unstructured":"Salton, G. and Buckley, C. (1988), \u201cTerm weighting approaches in automatic text retrieval\u201d, Information Processing and Management, Vol. 24 No. 5, pp. 513\u201023.","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"key2022031219421310900_b21","unstructured":"Saracevic, T. (1991), \u201cIndividual difference in organizing, searching and retrieving information\u201d, Proceedings of the 54th Annual Meeting of the American Society of Information Science, Washington DC, October, pp. 82\u20106."},{"key":"key2022031219421310900_b22","unstructured":"Shanfeng, Z., Xiaotie, D., Kang, C. and Weimin, Z. (2001), \u201cUsing online relevance feedback to build effective personalized metasearch engine\u201d, Proceedings of the Second Conference on Web Information Systems Engineering, Kyoto, December, pp. 262\u2010268."},{"key":"key2022031219421310900_b23","unstructured":"Vires, A. and Roelleke, T. (2005), \u201cRelevance information: a loss of entropy but a gain for IDF?\u201d, Proceedings of the Conference of SIGIR'05, Salvador, August, pp. 282\u2010289."},{"key":"key2022031219421310900_b24","doi-asserted-by":"crossref","unstructured":"Wilbur, W. (1996), \u201cHuman subjectivity and performance limits in document retrieval\u201d, Information Processing and Management, Vol. 32 No. 5, pp. 515\u201027.","DOI":"10.1016\/0306-4573(96)00028-3"},{"key":"key2022031219421310900_b25","doi-asserted-by":"crossref","unstructured":"Yu, C., Luk, W. and Cheung, T. (1976), \u201cA statistical model for relevance feedback in information retrieval\u201d, Journal of the ACM, Vol. 23 No. 2, pp. 273\u201086.","DOI":"10.1145\/321941.321947"}],"container-title":["Online Information Review"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/14684520910985701","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/14684520910985701\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/14684520910985701\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T00:41:18Z","timestamp":1753404078000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/oir\/article\/33\/4\/745-760\/314631"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,8,7]]},"references-count":25,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2009,8,7]]}},"alternative-id":["10.1108\/14684520910985701"],"URL":"https:\/\/doi.org\/10.1108\/14684520910985701","relation":{},"ISSN":["1468-4527"],"issn-type":[{"type":"print","value":"1468-4527"}],"subject":[],"published":{"date-parts":[[2009,8,7]]}}}