A punishment/reward based approach to ranking

ABSTRACT

One of the important challenges in current search engines is dealing with the "rich get richer" problem. In popularity-based ranking algorithms like PageRank, due to considering the structure of the web as the measure for ranking the pages, newly-created but highly-qualified pages are effectively disregarded shoot out, and can take a very long time before becoming popular. In this paper we present a new punishment/reward based approach that adds a new dimension to the PageRank model for reducing the effect of the rich get richer problem using implicit feedback of visitors. In this approach, in addition to considering the structure of links as a page-creator's point of view, we use the page-visitor's view as an important parameter to improve the accuracy of the PageRank algorithm.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms, Experimentation, Human Factors, Measurement

Keywords:
pagerank, ranking, relevance feedback, search engine