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Query Suggestion and Recommendation Using Bipartite Graph and K-Means Clustering
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Abstract: With the diverse and explosive growth of web information, retrieving, organizing and utilizing the information effectively and efficiently has become more and more critical. The first challenge is that it is not easy to recommend latent semantically relevant results to users. The second challenge is to take into account the personalization feature. As the exponential explosion of various contents generated on the Web, Recommendation techniques have become increasingly indispensable. Innumerable different kinds of recommendations are made on the Web every day, including movies, music, images, books recommendations, query suggestions, tags recommendations, etc., The proposed work carries out query suggestion and recommends query and URLβs using Bipartite graph and K- means clustering.
Keywords: Recommendation, Clustering, Query suggestion.
Keywords: Recommendation, Clustering, Query suggestion.
How to Cite:
[1] , βQuery Suggestion and Recommendation Using Bipartite Graph and K-Means Clustering,β International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
