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Volumn 10, Issue 4, 2011, Pages

User behaviors in related word retrieval and new word detection: A collaborative perspective

Author keywords

Collaborative filtering; Natural language processing; New word detection; Related words retrieval; User behaviors

Indexed keywords

CHINESE INPUT; COLLABORATIVE FILTERING; DATA SETS; DETECTION TASKS; MACHINE LEARNING COMMUNITIES; NATURAL LANGUAGE PROCESSING; RELATED WORD; SEMANTIC RELATEDNESS; USER BEHAVIOR ANALYSIS; USER BEHAVIORS; USER EXPERIENCE; WORD LISTS;

EID: 84855223743     PISSN: 15300226     EISSN: 15583430     Source Type: Journal    
DOI: 10.1145/2025384.2025388     Document Type: Review
Times cited : (4)

References (46)
  • 1
    • 20844435854 scopus 로고    scopus 로고
    • Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
    • DOI 10.1109/TKDE.2005.99
    • ADOMAVICIUS, G. AND TUZHILIN, A. 2005. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17, 6, 734-749. (Pubitemid 40860454)
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
  • 3
    • 35348903881 scopus 로고    scopus 로고
    • Measuring semantic similarity between words using web search engines
    • DOI 10.1145/1242572.1242675, 16th International World Wide Web Conference, WWW2007
    • BOLLEGALA, D., MATSUO, Y., AND ISHIZUKA, M. 2007. Measuring semantic similarity between words using web search engines. In Proceedings of the 16th International Conference on World Wide Web (WWW'07). 757-766. (Pubitemid 47582305)
    • (2007) 16th International World Wide Web Conference, WWW2007 , pp. 757-766
    • Bollegala, D.1    Matsuo, Y.2    Ishizuka, M.3
  • 6
    • 0008582840 scopus 로고    scopus 로고
    • Unknown word detection for Chinese by a corpus-based learning method
    • CHEN, K. AND BAI, M. 1998. Unknown word detection for Chinese by a corpus-based learning method. .Comput. Linguist. 3, 1, 27-44.
    • (1998) Comput. Linguist , vol.3 , Issue.1 , pp. 27-44
    • Chen, K.1    Bai, M.2
  • 7
    • 84936824188 scopus 로고
    • Word association norms, mutual information, and lexicography
    • CHURCH, K. AND HANKS, P. 1990.Word association norms, mutual information, and lexicography. Comput. .Linguist. 16, 1, 22-29.
    • (1990) Comput. .Linguist , vol.16 , Issue.1 , pp. 22-29
    • Church, K.1    Hanks, P.2
  • 9
    • 3042821101 scopus 로고    scopus 로고
    • Item-based top-n recommendation algorithms
    • DESHPANDE, M. AND KARYPIS, G. 2004. Item-based top-n recommendation algorithms. ACM Trans. Inf. .Sys. 22, 1, 143-177.
    • (2004) ACM Trans. Inf. .Sys. , vol.22 , Issue.1 , pp. 143-177
    • Deshpande, M.1    Karypis, G.2
  • 11
    • 2942731012 scopus 로고    scopus 로고
    • An extensive empirical study of feature selection metrics for text classification
    • FORMAN, G. 2003. An extensive empirical study of feature selection metrics for text classification. J. Mach.
    • (2003) J. Mach Learn. Res , vol.3 , pp. 1289-1305
    • Forman, G.1
  • 13
    • 84855210544 scopus 로고    scopus 로고
    • GOOGLE Google Sets
    • GOOGLE. 2010. Google Sets. http://labs.google.com/sets.
    • (2010)
  • 14
  • 17
    • 77956986937 scopus 로고    scopus 로고
    • Unsupervised semantic similarity computation between terms using Web documents
    • IOSIF, E. AND POTAMIANOS, A. 2010. Unsupervised semantic similarity computation between terms using Web documents. IEEE Trans. Knowl. Data Eng. 22, 11, 1637-1647.
    • (2010) IEEE Trans. Knowl. Data Eng. , vol.11 , Issue.22 , pp. 1637-1647
    • Iosif, E.1    Potamianos, A.2
  • 23
    • 69249119464 scopus 로고    scopus 로고
    • Learning to rank for information retrieval
    • LIU, T. 2009. Learning to rank for information retrieval. Found. Trends Inf. Retriev. 3, 3, 225-331.
    • (2009) Found. Trends Inf. Retriev , vol.3 , Issue.3 , pp. 225-331
    • Liu, T.1
  • 27
    • 24744469980 scopus 로고    scopus 로고
    • Power laws, Pareto distributions and Zipf's law
    • DOI 10.1080/00107510500052444
    • NEWMAN, M. 2005. Power laws, Pareto distributions and Zipf's law. Contemp. Phys. 46, 5, 323-351. (Pubitemid 41335662)
    • (2005) Contemporary Physics , vol.46 , Issue.5 , pp. 323-351
    • Newman, M.E.J.1
  • 34
    • 34250638291 scopus 로고    scopus 로고
    • A web-based kernel function for measuring the similarity of short text snippets
    • DOI 10.1145/1135777.1135834, Proceedings of the 15th International Conference on World Wide Web
    • SAHAMI, M. AND HEILMAN, T. 2006. A web-based kernel function for measuring the similarity of short text snippets. In Proceedings of the 15th International Conference on World Wide Web (WWW'06). 377-386. (Pubitemid 46946630)
    • (2006) Proceedings of the 15th International Conference on World Wide Web , pp. 377-386
    • Sahami, M.1    Heilman, T.D.2
  • 35
    • 0016572913 scopus 로고
    • A vector space model for automatic indexing
    • SALTON, G.,WONG, A., AND YANG, C. 1975. A vector space model for automatic indexing. Comm. ACM 18, 11, 613-620.
    • (1975) Comm ACM , vol.18 , Issue.11 , pp. 613-620
    • Salton, G.1    Wong, A.2    Yang, C.3
  • 38
    • 57749207907 scopus 로고    scopus 로고
    • Finding cars, goddesses and enzymes: Parametrizable acquisition of labeled instances for open-domain information extraction
    • VAN DURME, B. AND PAŞCA, M. 2008. Finding cars, goddesses and enzymes: Parametrizable acquisition of labeled instances for open-domain information extraction. In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI'08). 1243-1248.
    • (2008) Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI'08) , pp. 1243-1248
    • Van Durme, B.1    Paşca, M.2
  • 43
    • 36348971115 scopus 로고    scopus 로고
    • Improving similarity measures for short segments of text
    • AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
    • YIH, W. AND MEEK, C. 2007. Improving similarity measures for short segments of text. In Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI'07). 1489-1494. (Pubitemid 350149776)
    • (2007) Proceedings of the National Conference on Artificial Intelligence , vol.2 , pp. 1489-1494
    • Yih, W.-T.1    Meek, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.