Bayesian rough set based information retrieval

References

• Chatterjee, N., Yadav, N. (2018). Fuzzy rough set based sentence similarity measure and its application to text summarization. IETE Technical Review, 36(5), 517-525.
   Web of Science ®Google Scholar
• Chi, Y., Zhu, J., Huag, L., Xu, H. (2019). Concepts recommendation for searching scientific papers. Cluster Computing, 22, 8669-8675.
   Web of Science ®Google Scholar
• Dai, B. (2019). Research on Chinese and English language information retrieval algorithm based on bilingual theme model. Cluster Computing, 22, 3681-3688.
   Web of Science ®Google Scholar
• De Cock, M., Cornelis, C. (2005). Fuzzy rough set-based web query expansion. In: Proceedings of rough sets and soft computing in intelligent agent and web technology. International workshop at WIIAT, pp 9-16.
   Google Scholar
• El-Sayyad, S.E., Saleh, A.I., Ali, H.A. (2018). A new semantic web service classification (SWSC) strategy. Cluster Computing, 21(3), 1639–1665.
   Web of Science ®Google Scholar
• Formica, A. (2012). Semantic web search based on rough sets and fuzzy formal concept analysis. Knowledge-Based Systems, 26, 40-47.
   Web of Science ®Google Scholar
• Green, J., Horne, N., Ortowska, E., Siemens, P. (1996). A rough set model of information retrieval. Fundamenta Informaticae, 28(3-4), 273–296.
   Google Scholar
• Guo, K., Liang, Z., Tang, Y., Chi, T. (2018). SOR: an optimized semantic ontology retrieval algorithm for heterogeneous multimedia big data. Journal of Computer Science, 28, 455-465.
   Web of Science ®Google Scholar
• He, M., Feng, B. (2005). Intelligent information retrieval based on variable precision rough set model and fuzzy sets. In: Rough sets, fuzzy sets, data mining, and granular computing. RSFDGrC, LNCS, 3642, 184-192.
   Google Scholar
• Ho, T.B., Funakoshi, K. (1990). Information retrieval using rough sets. Journal of Japanese Society for AI, 23(102), 424-433.
   Google Scholar
• Jiang, Y. (2020). Semantically-enhanced information retrieval using multiple knowledge resources. Cluster Computing. https://doi.org/10.1007/s10586-020-03057-7
   Web of Science ®Google Scholar
• Kanagarajan, K., Arumugam, S. (2019). Intelligent sentence retrieval using semantic word based answer generation algorithm with cuckoo search optimization. Cluster Computing, 22, 7003-7013.
   Web of Science ®Google Scholar
• Li, Y., Zhang, C., Swan, J.R. (2000). An information filtering model on the web and its applications in JobAgent. Knowledge-Based Systems. 13, 285–296.
   Web of Science ®Google Scholar
• Ma, B., Zhang, N., Liu, G., Li, L., Yuan, H. (2016). Semantic search for public opinions on urban affairs: a probabilistic topic modeling based approach. Information Processing and Management, 52(3), 430–445.
   Web of Science ®Google Scholar
• Meng, X., Chen, Q.C., Wong, L. (2009). A tolerance rough set based semantic clustering method for web search results. Information Technology Journal, 8(4), 453-464.
   Google Scholar
• Melucci, M. (2009). Vector-Space Model. In: Liu L., Ozsu M.T. (eds.) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9
   Google Scholar
• Pawlak, Z. (1982). Rough sets. International Journal of Computer and Information Sciences, 11(5), 341-356.
   Web of Science ®Google Scholar
• Pawlak, Z. (2012). Rough set: theoretical aspects of reasoning about data (vol. 9). Springer Science & Business Media.
   Google Scholar
• Rahman, A., Beg, M.M.S. (2014). Face sketch recognition using sketching with words. International Journal of Machine Learning and Cybernetics, 6(4), 597-605.
   Web of Science ®Google Scholar
• Rani, P.S., Suresh, R.M., Sethukarasi, R. (2019). Multi-level semantic annotation and unified data integration using semantic web ontology in big data processing. Cluster Computing, 22, 10401-10413.
   Web of Science ®Google Scholar
• Rajendran, V., Swaminathan, S. (2014). MOSS-IR: Multi-Ontology Based Search System for Information Retrieval in E-health Domain. In: ICGHIA. Elsevier, pp. 179-187.
   Google Scholar
• Singh, S., Dey, L. (2003). A rough–fuzzy document grading system for customized text information retrieval. Information Processing and Management, 25(4), 347–361.
   Google Scholar
• Slezak, D., Ziarko, W. (2002). Bayesian rough set model. In: Proceeding of international workshop on foundation of data mining (FDM’2002), Japan, pp 131–135.
   Google Scholar
• Slezak, D., Ziarko, W. (2005). The investigation of the Bayesian rough set model. International Journal of Approximate Reasoning, 40(1-2), 81–91.
   Web of Science ®Google Scholar
• Srikanth, D., Sakthivel, S. (2019). Vantage Point Latent Semantic Indexing for multimedia web document search. Cluster Computing, 22, 10587-10594.
   Web of Science ®Google Scholar
• Srinivasan, P. (1989). Intelligent information retrieval using rough sets approximations. Information Processing and Management, 25(4), 347–361.
   Web of Science ®Google Scholar
• Srinivasan, P., Ruiz, M.E., Kraft, D.H., Chen, J., Kundu, S. (2001). Vocabulary mining for information retrieval: rough sets and fuzzy sets. Information Processing and Management, 37(1), 15-38.
   Web of Science ®Google Scholar
• Wong, S.K.M., Ziarko, W. (1986). A machine learning approach to information retrieval. In: Proceeding of ACM SIGIR conference, Italy, pp. 228–233.
   Google Scholar
• Yao, Y.Y., Wong, S.K.M., Lingras, P. (1990). A decision-theoretic rough set model. In: Ras, Z.W., Zemankova, M., Emrich, M.L. (eds), Methodologies for Intelligent Systems, vol. 5, pp. 17–24.
   Google Scholar
• Yadav, N., Chatterjee, N. (2018). Fuzzy rough set based technique for user specific information retrieval: a case study on Wikipedia data. International Journal of Rough sets and Data Analysis, 5(4), 1-16.
   Google Scholar
• Zhou, B., Yao, Y.Y. (2010). Evaluating information retrieval system performance based on user preference. Journal of Intelligent Information Systems, 34(3), 227-248.
   Web of Science ®Google Scholar
• Ziarko, W. (1993). Variable precision rough sets model. Journal of Computer and Systems Sciences, 46(1), 39–59.
   Web of Science ®Google Scholar
• Ziarko, W., Fei, X. (2002). VPRSM approach to WEB searching. In: Proceedings of third International conference on rough sets and current trends in computing, RSCTC’02, LNCS, 2475, pp 514–521.
   Google Scholar
• Debaditya Barman, Ritam Sarkar, Anil Tudu & Nirmalya Chowdhury (2020). Personalized query recommendation system: A genetic algorithm approach, Journal of Interdisciplinary Mathematics, 23:2, 523 535, DOI: 10.1080/09720502.2020.1731964.
   Web of Science ®Google Scholar
• Chengfeng Jian, Chunxia Pang & Meng Tao (2014). Directed Hypergraph-Based STEP Product Semantic Visual Analysis, Journal of Discrete Mathematical Sciences and Cryptography, 17:4, 363-378, DOI: 10.1080/09720529.2014.952518.
   Google Scholar
• Li Yan, Ying-Jiang Li, Xiang Yang & Wei Gao (2016). Gradient descent technology for sparse vector learning in ontology algorithms, Journal of Discrete Mathematical Sciences and Cryptography, 19:3, 753–775, DOI: 10.1080/09720529.2016.1178934.
   Web of Science ®Google Scholar
• Weibin Deng, Haijin Wang & Shimin Dai (2018). A prediction method for the cellphone replacement: Rough set-based analysis, Journal of Discrete Mathematical Sciences and Cryptography, 21:4, 881-893, DOI: 10.1080/09720529.2018.1491099.
   Web of Science ®Google Scholar