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Due to the rapid growth of web services in repositories, discovering the requisite web service is becoming increasingly cumbersome task. It has raised the demand for efficient web service clustering algorithms. In service repositories, when related web services are stored in a clustered way, it enhances the web service discovery process by reducing search space and time. Many eminent researchers have worked in this field and used the Term Frequency – Inverse Document Frequency (TF-IDF) method for representing web services in vector space. In general, there are various limitations of the TF-IDF approach i.e. (1) Not efficient for large documents (2) Position of term and its co-occurrences does not matter (3) Unable to analyze how terms are dispersed in different documents. In the web service scenario, services are represented in short text form. TF-IDF does not work well in web service representation because …