Abstract
In this present era of Big Data, different search engine users have different information requirements at different intervals of time. Thus, search results should be adapted to user’s requirements [1, 2]. In this research work, we propose a novel approach to adaptive web search augmented with capabilities of carrying out Big Data Analytics using second generation HDFS. Moreover, unlike conventional personalization techniques, the proposed approach does not require additional efforts from user such as reporting feedback/ratings etc. The proposed system can be implemented in the form of Intelligent Meta Search System (IMSS Tool) to overcome the problem of irrelevant web page retrieval faced by user of generic search engines. An extensive experimental evaluation shows that the average ranking precision of adaptive IMSS tool improves with trial runs when compared with a popular search engine.
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Malhotra, D., Rishi, O.P. (2017). IMSS: A Novel Approach to Design of Adaptive Search System Using Second Generation Big Data Analytics. In: Modi, N., Verma, P., Trivedi, B. (eds) Proceedings of International Conference on Communication and Networks. Advances in Intelligent Systems and Computing, vol 508. Springer, Singapore. https://doi.org/10.1007/978-981-10-2750-5_20
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DOI: https://doi.org/10.1007/978-981-10-2750-5_20
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