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References
Lancaster, F. (1972). Vocabulary control for information retrieval. Washington, D.C.: Information Resources Press.
Cleverdon, C., Mills, J. & Keen, E. (1966). Factors determining the performance of indexing systems, vol. 1: design, vol. 2: test results. Cranfield, England: Aslib Cranfield Research Project
Cleverdon, C. (1997) The Cranfield tests on indexing language devices. In K. Sparck Jones & P. Willett (Eds.), Readings in information retrieval (pp. 47–59). San Francisco: Morgan Kaufnann Publishers, Inc.
Luhn, H. (1957). A statistical approach to mechanized encoding and searching of literary information. IBM Journal, 309–317.
Edmundson, H. & Wyllys, R. (1961). Automatic abstracting and indexing—survey and recommendations. Communications of the ACM, 4, 226–234.
Carroll, J. & Roeloffs, R. (1969). Computer selection of keywords using word-frequency analysis. American Documentation, 227–233.
Stevens, M. (1965). Automatic indexing: a state-of-the-art report. NBS Monograph 91. Washington, D.C.
Salton, G. & Lesk, M. (1968). Computer evaluation of indexing and text processing. Journal of the Association of Computer Machinery, 15, 8–36.
Sparck Jones, K.S. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28(1), 11–21.
Salton, G. & Yang, C. (1973). On the specification of term values in automatic indexing. Journal of Documentation, 29(4), 351–372.
Sparck Jones, K.S. (1973). Index term weighting. Information Storage and Retrieval, 9, 619–633.
Maron, M. & Kuhns, J. (1960). On relevance, probabilistic indexing and information retrieval. Journal of the Association of Computer Machinery, 7, 216–244.
Robertson, S. & Sparck Jones, K. (1976). Relevance weighting of search terms. Journal of the American Society for Information Science, 27(3), 129–146.
Sparck Jones, K. (1979). Search term relevance weighting given little relevance information. Journal of Documentation, 35(1).30–48.
Croft, W. & Harper, D. (1979). Using probabilistic models of document retrieval without relevance information. Journal of Documentation, 35(4), 285–295.
Harper, D. (1980). Relevance feedback in document retrieval systems: an evaluation of probabilistic strategies. (Doctoral dissertation, Jesus College, Cambridge, England (1980).
Croft, W. (1983). Experiments with representation in a document retrieval system. Information Technology: Research and Development, 2(1), 1–21.
Salton, G. & Buckley, C. (1988). Term-weighting approaches in automatic text processing. Information Processing and Management, 24(5), 513–523.
Harman, D. (1986). An experimental study of factors important in document ranking. In Proceedings of the ACM conference on research and development in information retrieval, 186–193.
Dennis, S. (1964). The construction of a thesaurus automatically from a sample of text. In Proceedings of the statistical association methods for mechanized documentation. National Bureau of Standards Miscellaneous Publication 269.
Salton, G. & McGill, M. (eds). (1983). Introduction to modern information retrieval.. McGraw-Hill, New York, NY: McGraw-Hill.
Lockbaum, K. & Streeter, L. (1989). Comparing and combining the effectiveness of latent semantic indexing and the ordinary vector space model for information retrieval. Information Processing and Management, 25(6), 665–676.
Smith, M. & Dimmick, D. (1997) A study of factors important in document ranking (revisited). (unpublished report of work done at NIST) Harman, D. (1993). Overview of the first Text REtrieval Conference (TREC-1). In Proceedings of the first Text REtrieval Conference (TREC-1), 1–20.
Robertson, S., Walker, S., Hancock-Beaulieu, & Gatford, M. (1994). Okapi and TREC-2. In Proceedings of the Second Text REtrieval Conference (TREC-2), 21–34.
Robertson, S. & Walker, S. (1994). Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval. In Proceedings of the 17th annual international ACM SIGIR conference on research and development in information retrieval, 232–241.
Sparck Jones, K., Walker, S. & Robertson, S. (2000). A probabilistic model of information retrieval: development and comparative experiments, parts 1 and 2. Information Processing and Management, 36(6), 779–840.
Hiemstra, D. & de Vries, (2000) A. Relating the new language models of information retrieval to the traditional retrieval models. Technical Report TR-CTIT-0-9, Centre for Telematics and Information Retrieval.
Savoy, J. (2003). Cross-language information retrieval: experiments based on CLEF 2000 corpora. Information Processing and Management, 39(1), 75–116.
Chen, K. & Chen, H.(2001). Cross-language Chinese text retrieval in NTCIR Workshop-towards cross-language multilingual text retrieval. SIGIR Forum 32(2), 12–19.
McKeown, K., Klavan, J., Hatzivassiloglou, V., Barzilay, R. & Eskin, E. (1999) Towards multidocument summarization by reformulation: progress and prospects. In Proceedings of the 17th national congress on artificial intelligence (AAAI-99).
Tzoukermann, E., Muresan, S. & Klavans, J. (2001). GIST-IT summarizing email using linguistic knowledge and machine learning. In Proceedings of the ACL 2001 Workshop on Evaluation Methods for Language and Dialog Systems.
Zechner, K. & Waibel, A. (2000). DIASUMM: flexible summarization of spontaneous dialogues in unrestricted domains. In Proceedings of COLING 2000, 968–974.
Xu, J., Licuanan, A. & Weischedel, R. (2003). Evaluation of an extraction-based approach to answering definitional questions. In Proceedings of the 27th annual international ACM SIGIR conference on research and development in information retrieval, 418–424
Downie, S. & Nelson, M. (2000). Evaluation of a simple and effective music information retrieval method. In Proceedings of the 23th annual international ACM SIGIR conference on research and development in information retrieval. 73–80.
Muller, H., Squire, D., Muller, W. & Pun, T. (1999). Efficient access methods for content-based image retrieval with inverted files. In Proceedings of the SPIE Symposium on Voice, Video and Data Communication. 461–472.
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Harman, D. (2005). The History of IDF and Its Influences on IR and Other Fields. In: Tait, J.I. (eds) Charting a New Course: Natural Language Processing and Information Retrieval. The Kluwer International Series on Information Retrieval, vol 16. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3467-9_5
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