Text Clustering with Query Expansion Using Scontext Formulated Query Weighted Approach

Text clustering is a technique used to gather the documents which have similar content. The main objective of text clustering is to divide the unstructured set of objects into clusters. The algorithm can be used to represent the concept and to measure the similarity among the concept present in the document. The clustering process is widely applied for summarizing the corpus and document classification. Traditionally, quantitative data are focused for clustering, which contain numeric data as their attributes. Following this, categorical data are also studied where the attributes hold the nominal values. Nevertheless, these techniques do not work well for clustering the text data. Since the text data has the following unique properties, it requires a specialized algorithm for the task.