Abstract
Data is uploaded to Internet daily that make more and more difficult to mine it. Currently, the available of data mining tools still cannot discover knowledge from data that need semantic with difference dimensions. In this paper we present a method to search the related documents based on clustering that grouped by content. In this, the features are assigned weight by supporting. Experimental results show that the proposed method is really effective, high accuracy and the response results are quickly.
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References
Bhattacharyya, P., Datta, J.: Ranking in information retrieval, 16 April 2010
Ceri, S., Bozzon, A., Brambilla, M., Della Valle, E., Fraternali, P., Quarteroni, S.: Web Information Retrieval. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39314-3. ISBN 978-3-642-39314-3
Buscher, G., Dengel, A., van Elst, L.: Query expansion using gaze-based feedback on the subdocument level. In: Proceedings of the 31th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM Press, Singapore, pp. 387–394 (2008)
Zadeh, M.V.: Improving the performance of text Information Retrieval (IR) System, Ph.D thesis. Porto University (2012)
Lau, J.H., Newman, D., Karimi, S., Baldwin, T.: Best topic word selection for topic labelling, Coling 2010, Posters, pp. 605–613 (2010)
Moens, M.-F., Vulić, I.: Monolingual and cross-lingual probabilistic topic models and their applications in information retrieval. In: Serdyukov, P., Braslavski, P., Kuznetsov, S.O., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., Yilmaz, E. (eds.) ECIR 2013. LNCS, vol. 7814, pp. 874–877. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-36973-5_106
Park, H., et al.: Agglomerative hierarchical clustering for information retrieval using latent semantic index. In: 2015 IEEE International Conference Smart City/Socialcom/Sustaincom (SmartCity), 19–21 December 2015
Kalyanasundaram, C., Ahire, S., Jain, G., Jain, S.: Text clustering for information retrieval system using supplementary information. Int. J. Comput. Sci. Inf. Technol. 6(2), 1613–1615 (2015)
Kuhn, L., Eickhoff, C.: Implicit negative feedback in clinical information retrieval. In: Medical Information Retrieval Workshop (MedIR), Pisa, Italy, 21 July 2016
Rocchio, J.J.: Relevance feedback in information retrieval (1971)
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Bui, K.L., Nguyen, T.N.T., Nguyen, T.T.H., Dao, T.T. (2018). An Effective of Data Organizing Method Combines with Naïve Bayes for Vietnamese Document Retrieval. In: Cong Vinh, P., Ha Huy Cuong, N., Vassev, E. (eds) Context-Aware Systems and Applications, and Nature of Computation and Communication. ICTCC ICCASA 2017 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-77818-1_20
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DOI: https://doi.org/10.1007/978-3-319-77818-1_20
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