[1] Resnik P., WSD in NLP applications, In: Agirre E., Edmonds P. (Eds.), Word Sense Disambiguation: Algorithms and Applications, Dordrecht: Springer Netherlands, 2006, 299-337Google Scholar
[2] Mothe J., Tanguy L., Linguistic features to predict query difficulty - a case study on previous TREC campaigns, ACM Conference on research and Development in Information Retrieval, SIGIR, Predicting query difficulty - methods and applications workshop, Salvador de Bahia, Brazil, ACM, 2005, 7-10Google Scholar
[3] Chifu A.-G., Hristea F., Mothe J., Popescu M., Word sense discrimination in information retrieval: a spectral clustering-based approach, Information Processing & Management, 2015, 51(2), 16-31Google Scholar
[4] Tyar S. M., Than M. M., Sense-based information retrieval system by using Jaccard coefficient based WSD algorithm, In: Proceedings of 2015 International Conference on Future Computational Technologies, ICFCT’15, 2015, 197-203Google Scholar
[5] Matinfar F., Hybrid sense disambiguation in web queries, Bulletin de la Société Royale des Sciences de Liège, 2016, 85, 1165-1175Google Scholar
[6] Stokoe C., Oakes M. P., Tait J., Word sense disambiguation in information retrieval revisited, In: SIGIR, ACM, 2003, 159-166Google Scholar
[7] Guyot J., Falquet G., Radhouani S., Benzineb K., Analysis of word sense disambiguation-based information retrieval, In: Peters C., Deselaers T., Ferro N., Gonzalo J., Jones G. J. F., Kurimo M. (Eds.), CLEF, Lecture Notes in Computer Science, Springer, 2008, 5706, 146-154Google Scholar
[8] Zhong Z., Ng H. T., Word sense disambiguation improves information retrieval, In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1 (ACL ’12), Association for Computational Linguistics, Stroudsburg, PA, USA, 2012, 273-282Google Scholar
[9] Mihalcea R., Moldovan D., Semantic indexing using WordNet senses, In: Proceedings of the ACL-2000 workshop on Recent Advances in Natural Language Processing and Information Retrieval: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 11, Association for Computational Linguistics, Stroudsburg, PA, USA, 2000, 35-45Google Scholar
[10] Kim S.-B., Seo H.-C., Rim H.-C., Information retrieval using word senses: root sense tagging approach, In: Proceedings of the 27th annual international ACM SIGIR conference on Research and Development in Information Retrieval, ACM, 2004, 258-265Google Scholar
[11] Schütze H., Pedersen J. O., Information retrieval based on word senses, In: Proceedings of the 4th annual Symposium on Document Analysis and Information Retrieval, 1995, 161-175Google Scholar
[12] Chifu A.-G., Ionescu R.-T., Word sense disambiguation to improve precision for ambiguous queries, Central European Journal of Computer Science, 2012, 2(4), 398-411Google Scholar
[13] Schütze H., Automatic word sense discrimination, Journal of Computational Linguistics, 1998, 24(1), 97-123Google Scholar
[14] Luxburg U., A tutorial on spectral clustering, Statistics and Computing, 2997, 17(4), 395-416Google Scholar
[15] Hastie T., Tibshirani R., Friedman J., The Elements of Statistical Learning: Data Mining, Inference and Prediction (2nd edition), New York, USA: Springer-Verlag, 2009Google Scholar
[16] Popescu M., Hristea F., State of the art versus classical clustering for unsupervised word sense disambiguation, Artificial Intelligence Review, 2011, 35(3), 241-264Web of ScienceCrossrefGoogle Scholar
[17] Maier M., Hein M., Luxburg U., Optimal construction of knearest- neighbor graphs for identifying noisy clusters, Theoretical Computer Science, 2009, 410(19), 1749-1764Google Scholar
[18] Màrquez L., Escudero G., Martínez D., Rigau G., Supervised corpus-based methods forWSD, In: Agirre E., Edmonds P. (Eds.), Word Sense Disambiguation, Text, Speech and Language Technology, Springer, Dordrecht, 2007, 33, 167-216Google Scholar
[19] Goyal K., Hovy E. H., Unsupervised word sense induction using distributional statistics, In: Hajic J., Tsujii J (Eds.), Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), Technical Papers, ACL, 2014, 1302-1310Google Scholar
[20] Shaw J. A., Fox E. A., Combination of multiple searches, In: Overview of the 3rd Text Retrieval Conference, 1995, 105-108Google Scholar
[21] Mothe J., Tanguy L., Linguistic analysis of users’ queries: towards an adaptive information retrieval system, In: International Conference on Signal Image Technology and Internebased Systems (SITIS), South-East European Research Center (SEERC), 2007, 77-84Google Scholar
[22] Attar R., Fraenkel A. S., Local feedback in full-text retrieval systems, Journal of the ACM, 1977, 24(3), 397-417CrossrefGoogle Scholar
[23] Buckley C., Salton G., Allan J., Singhal A., Automatic query expansion using SMART: TREC 3, In: Proceedings of The third Text REtrieval Conference (TREC-3), 1994, 69-80Google Scholar
[24] Hristea F., Popescu M., Dumitrescu M., Performing word sense disambiguation at the border between unsupervised and knowledge-based techniques, Artificial Intelligence Review, 2008, 30(1), 67-86Web of ScienceCrossrefGoogle Scholar
[25] Banerjee S., Pedersen T., Extended gloss overlaps as a measure of semantic relatedness, In: Proceedings of the 18th International Joint Conference On Artificial Intelligence, 2003, 805-810Google Scholar
[26] Preot,iuc-Pietro D., Hristea F., Unsupervised word sense disambiguation with n-gram features, Artificial Intelligence Review, 2014, 41(2), 241-260.Google Scholar
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