The number of vertical search engines and portals has rapidly increased over the last years, making the importance of a topic-driven (focused) crawler evident. In this paper, we develop a latent semantic indexing classifier that combines link analysis with text content in order to retrieve and index domain specific web documents. We compare its efficiency with other well-known web information retrieval techniques. Our implementation presents a different approach to focused crawling and aims to overcome the limitations of the necessity to provide initial training data while maintaining a high recall/precision ratio. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Almpanidis, G., & Kotropoulos, C. (2005). Combining text and link analysis for focused crawling. In Lecture Notes in Computer Science (Vol. 3686, pp. 278–287). Springer Verlag. https://doi.org/10.1007/11551188_30
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