Clustering algorithms are used to generate clusters of elements having similar characteristics. Among the different groups of clustering algorithms, agglomerative algorithm is widely used in the document clustering domain. This study aimed to examine the effectiveness of agglomerative clustering algorithm in document clustering by enhancing its efficiency and evaluating it through implementation. The resulting values, precision = 0.8571, recall = 0.8571 and F-measure = 0.857076 indicate the highest level of accuracy and efficiency compared to existing algorithm.
Keywords
Cosine Similarity Measure, Document Clustering, F-Measure, Hierarchical Agglomerative Clustering, Preprocessing, TF-IDF.
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