A Survey On Web Personalization For Recommendations Essay

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A SURVEY ON WEB PERSONALIZATION FOR RECOMMENDATIONS ABSTRACT Data mining is a process of extracting the information from the large set of databases. As the web contain huge amount of information finding the exact information of which user required is difficult. Web personalization is a process of analyzing the user?s navigational behavior based on web sequence access performed by the user based on which recommendations are done. Web usage mining plays an important role in recommendation of pages to user based on user interest. Different kinds of technics and algorithms are used for web personalization and recommendation of pages. The technics of data mining such as collaborative filtering, association rule mining, ontology, support vector machine, sequence access patterns and web log mining are compared to know which technic is more efficient for recommendation of web pages based on web personalization. A survey conducted to find which technic easily recommends the web pages to user such that it consumes less time for searching the information. The paper proposes the technic that provides efficient results for recommendation of pages to user based on user interest comparing parameters like precision and recall and matching algorithm. Web log based recommendations are more efficient when compared to other technics as it consumes less time for searching the relevant information. The survey gives the result in the form of the graph for different parameters. Index Terms:
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