Enhancing the Labelling Technique of Suffix Tree Clustering Algorithm
R. Mahalakshmi, Lakshmi Praba V · International Journal of Data Mining & Knowledge Management Process · 2014
Clustering the results of a search helps the user to overview the information returned.In this paper, we look upon the clustering task as cataloguing the search results.By catalogue we mean a structured label list that can help the user to realize the labels and search results.Labelling Cluster is crucial because meaningless or confusing labels may mislead users to check wrong clusters for the query and lose extra time.Additionally, labels should reflect the contents of documents within the cluster accurately.To be able to label clusters effectively, a new cluster labelling method is introduced.More emphasis was given to /produce comprehensible and accurate cluster labels in addition to the discovery of document clusters.We also present a new metric that employs to assess the success of cluster labelling.We adopt a comparative evaluation strategy to derive the relative performance of the proposed method with respect to the two prominent search result clustering methods: Suffix Tree Clustering and Lingo.we perform the experiments using the publicly available Datasets Ambient and ODP-239