Abstract
In this work we compare different techniques to automatically find candidate web pages to substitute broken links. We extract information from the anchor text, the content of the page containing the link, and the cache page in some digital library. The selected information is processed and submitted to a search engine. We have compared different information retrieval methods for both, the selection of terms used to construct the queries submitted to the search engine, and the ranking of the candidate pages that it provides, in order to help the user to find the best replacement. In particular, we have used term frequencies, and a language model approach for the selection of terms; and cooccurrence measures and a language model approach for ranking the final results. To test the different methods, we have also defined a methodology which does not require the user judgments, what increases the objectivity of the results.
This work has been partially supported by the Spanish Ministry of Science and Innovation within the project QEAVis-Catiex (TIN2007-67581-C02-01) and the Regional Government of Madrid under the Research Network MAVIR (S-0505/TIC-0267).
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Martinez-Romo, J., Araujo, L. (2010). Analyzing Information Retrieval Methods to Recover Broken Web Links. In: Gurrin, C., et al. Advances in Information Retrieval. ECIR 2010. Lecture Notes in Computer Science, vol 5993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12275-0_6
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DOI: https://doi.org/10.1007/978-3-642-12275-0_6
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