Applying an Enhanced Algorithm for Mining Incremental Updates on an Egyptian Newspaper Website

Abstract—This paper presents new approaches for analyzing Egyptian Newspaper websites and presenting the most interesting topics that attract the largest portion of reading population to their newspaper website. The paper also presents techniques used for text and news mining. We first start with topic detection and tracking techniques to collect the reader website navigation data for the various topics then we use the proposed incremental algorithm (PIA), our previously published algorithm that was implemented in our previous researches, for mining of the news database. The paper concludes with significant results for identifying the readers trends, thus can dynamically display the most expected and required headline topics to the reader. The paper discovers also the most important topics for the users. Moreover, the paper had a significant effect for guiding the newspaper for the appropriate method for modifying its website to be dynamic according to the user interests specified by the association rules algorithm. We believe that this work had high impact in increasing the number of visitors for the newspaper website and attracting the reader's attention.