Evaluating Performance of Partition Based Document Clustering Algorithms for Information Retrieval
P. Prabhu · SSRN Electronic Journal · 2011
Information Retrieval (IR) is an emerging sub-field of information science concerning representation, storage; access and retrieval of information. Current research areas within the field of IR include searching and querying, ranking of search results, navigating and browsing information, optimizing information representation and storage and document classification and clustering. Within information retrieval, clustering of documents has several promising applications, all concerned with improving efficiency and effectiveness of the retrieval process. This paper focus on performance evaluation of two Partition based Document clustering algorithms. Firstly, various steps for pre-processing the documents for clustering are discussed. Second Partition based algorithms like k-means and Spherical k-means a variant of the k-means algorithm that uses cosine similarity is discussed. Finally, the performance evaluation of the algorithm is investigated with different execution of the program on the various document collections as a post processing. The execution time for each algorithm is also analyzed and the results are compared with one another.