Performance Evaluation of Web Search Result Clustering and Labeling

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Provided by: International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Topic: Big Data
Format: PDF
Web search results clustering is an increasingly popular technique for providing useful grouping of web search results. This paper introduces a prototype web search results clustering engine. Proposed clustering algorithm MFPF is compared against two other established web document clustering algorithms: major goal of the experiment is to determine the quality of results given by the system from the common user's point of view. The authors compare the results with ground truth of users' survey and comparing the results of different algorithms, such as Suffix Tree Clustering (STC) and Lingo and k-means.
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