Abstract
Term weighting schemes are the integral part of an Information retrieval system which play an important role in the performance of the information retrieval system. Manning et al (2002) and Sandor Dominich (2008) have provided a detail of information retrieval techniques and weighting schemes in their books. Weight of a term can be seen in two different aspects, local and global. Local weights are functions of frequency of a word in a document and global weights are functions of the frequency of a term in the entire collection. A detail discussion on different types of local weighting schemes can be found in Chisholm & Kolda (1999). Suitability of some global weighting schemes for local weights can be seen in Bisht et al (2008). A comparative study on term weighting schemes for text categorization has been made by Lan et al (2005). There are several weighting schemes, following are some of the commonly used local weighting schemes.
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References
Bisht R.K. and Dhami H S. On some properties of content words in a document. In Proceedings of the 6th Annual conference of Information Science and Technology Management, 2008
Chisholm, E. and Kolda T. G. New term weighting formulas for the vector space method in information retrieval. Technical report ORNL-TM-13756, Oak Ridge national laboratory, Oak ridge, TN, 1999
Dominich Sandor. The Modern Algebra of Information Retrieval (Information Retrieval Series).Springer-verlag, New York, 2008
Kim Hee-soo, Choi Ikkyu and Kim Minkoo. Refining Term Weights of Documents Using Term Dependencies. In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2004
Lan Man, Sung Sam-Yuan, Low Hwee-Boon and Tan Chew-Lim. A comparative study on term weighting schemes for text categorization. In Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2005
Manning C.D. and Schutze H. Foundations of Statistical Natural Language Processing. MIT press, Cambridge 2002
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Bisht, R.K., Pande, J. (2011). Local weighting scheme for word pairs. In: Pise, S.J. (eds) Thinkquest~2010. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-989-4_30
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DOI: https://doi.org/10.1007/978-81-8489-989-4_30
Publisher Name: Springer, New Delhi
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