Abstract
Fusion is the concept of combining data from more than one source. Data fusion is the process of integrating multiple sources of information such that their combination yields better results than if the data sources are used individually. Retrieving the efficient and effective data from World Wide Web is very difficult because day by day the amount of data increases at a very high speed. The focus of this paper is to implement fusion of text snippets, page count, semantic similarity, k-means clustering, and map reduction to improve the efficiency of the search result. The advantage of this approach is that it provides an easy integration of web contents and data sharing.
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Gomathi, B., Sakthivel, P. (2016). Implementing Fusion to Improve the Efficiency of Information Retrieval Using Clustering and Map Reduction. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_79
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DOI: https://doi.org/10.1007/978-81-322-2656-7_79
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