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A Novel Web Page Analysis Method for Efficient Reasoning of User Preference

  • Seunghwa Lee
  • Minchul Jung
  • Eunseok Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5068)

Abstract

The amount of information on the Web is rapidly increasing. Recommender systems can help users selectively filter this information based on their preferences. One way to obtain user preferences is to analyze characteristics of content that is accessed by the user. Unfortunately, web pages may contain elements irrelevant to user interests (e.g., navigation bar, advertisements, and links.). Hence, existing analysis approaches using the TF-IDF method may not be suitable. This paper proposes a novel user preference analysis system that eliminates elements that repeatedly appear in web pages. It extracts user interest keywords in the identified primary content. Also, the system has features that collect the anchor tag, and track the user’s search route, in order to identify keywords that are of core interest to the user. This paper compares the proposed system with pure TF-IDF analysis method. The analysis confirms its effectiveness in terms of the accuracy of the analyzed user profiles.

Keywords

Recommendation system User preference User profile TF-IDF 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Seunghwa Lee
    • 1
  • Minchul Jung
    • 1
  • Eunseok Lee
    • 1
  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwonSouth Korea

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