Abstract
The PageRank algorithm, used in the Google Search Engine, plays an important role in improving the quality of results by employing an explicit hyperlink structure among the Web pages. The prestige of Web pages defined by PageRank is derived solely from surfers’ random walk on the Web Graph without any textual content consideration. However, in the practical sense, user surfing behavior is far from random jumping. In this paper, we propose a link analysis that takes the textual information of Web pages into account. The result shows that our proposed ranking algorithms perform better than the original PageRank.
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Xu, Y., Umemura, K. (2005). Literal-Matching-Biased Link Analysis. In: Myaeng, S.H., Zhou, M., Wong, KF., Zhang, HJ. (eds) Information Retrieval Technology. AIRS 2004. Lecture Notes in Computer Science, vol 3411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31871-2_14
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DOI: https://doi.org/10.1007/978-3-540-31871-2_14
Publisher Name: Springer, Berlin, Heidelberg
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