Authors : Tawfiq A. Al-Asadi, Ahmed J. Obaid and Ahmad A. Al-Khayatt
Abstract: With explosive growth of information in World Wide Web and large host numbers continuously added to the internet which has different types of content such as text, images, audio, videos and others made the process of analysis web data very complex and difficult process. Analysis of web data also is very important task which required by many organizations, academic centers, companie’s, agencies, etc., for various task such as enhanced searching process, monitoring and business application. Therefore, many algorithms has proposed in recent research works to construct a model used for knowledge discovering from a corpus of web pages which might exist in different structured forms. The process of extracting web pages features and grouping similar web pages having similar interesting features called web page clustering. In this study, latent semantic analysis has been considered which has applied successfully in many text documents applications by first applying web pages mining process to our selected web pages corpus then text mining process are applied to represent web pages in a Vector Space Model (VSM), finally, K-means algorithm proposed to grouping similar web pages which are exist in semantic space.
Tawfiq A. Al-Asadi, Ahmed J. Obaid and Ahmad A. Al-Khayatt, 2017. Proposed Method for Web Pages Clustering using Latent Semantic Analysis. Journal of Engineering and Applied Sciences, 12: 8270-8277.