Abstract
We examine more-like-this information needs in different scenarios. A more-like-this information need occurs, when the user sees one interesting document and wants to access other but similar documents. One of our foci is on comparing different strategies to identify related web content. We compare following links (i.e., crawling), automatically generating keyqueries for the seen document (i.e., queries that have the document in the top of their ranks), and search engine operators that automatically display related results. Our experimental study shows that in different scenarios different strategies yield the most promising related results.
One of our use cases is to automatically support people who monitor right-wing content on the web. In this scenario, it turns out that crawling from a given set of seed documents is the best strategy to find related pages with similar content. Querying or the related-operator yield much fewer good results. In case of news portals, however, crawling is a bad idea since hardly any news portal links to other news portals. Instead, a search engine’s related operator or querying are better strategies. Finally, for identifying related scientific publications for a given paper, all three strategies yield good results.
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References
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of VLDB 1994, pp. 487–499 (1994)
Arasu, A., Cho, J., Garcia-Molina, H., Paepcke, A., Raghavan, S.: Searching the web. ACM Trans. Internet Technol. 1(1), 2–43 (2001)
Bendersky, M., Croft, W.B.: Finding text reuse on the web. In: Proceedings of WSDM 2009, pp. 262–271 (2009)
Dasdan, A., D’Alberto, P., Kolay, S., Drome, C.: Automatic retrieval of similar content using search engine query interface. In: Proceedings of CIKM 2009, pp. 701–710 (2009)
Fuhr, N., Lechtenfeld, M., Stein, B., Gollub, T.: The optimum clustering framework: Implementing the cluster hypothesis. Information Retrieval 15(2), 93–115 (2011)
Gollub, T., Hagen, M., Michel, M., Stein, B.: From keywords to keyqueries: Content descriptors for the web. In: Proceedings of SIGIR 2013, pp. 981–984 (2013)
Golshan, B., Lappas, T., Terzi, E.: SOFIA search: A tool for automating related-work search. In: Proceedings of SIGMOD 2012, pp. 621–624 (2012)
Hagen, M., Stein, B.: Candidate document retrieval for web-scale text reuse detection. In: Grossi, R., Sebastiani, F., Silvestri, F. (eds.) SPIRE 2011. LNCS, vol. 7024, pp. 356–367. Springer, Heidelberg (2011)
Lee, Y., Jung, H.Y., Song, W., Lee, J.H.: Mining the blogosphere for top news stories identification. In: Proceedings of SIGIR 2010, pp. 395–402 (2010)
Mihalcea, R., Tarau, P.: Textrank: Bringing order into texts. In: Proceedings of EMNLP 2004, pp. 404–411 (2004)
O’Callaghan, D., Greene, D., Conway, M., Carthy, J., Cunningham, P.: Uncovering the wider structure of extreme right communities spanning popular online networks. In: Proceedings of WebSci 2013, pp. 276–285 (2013)
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the web. Technical Report 1999-66, Stanford InfoLab (1999)
Pickens, J., Cooper, M., Golovchinsky, G.: Reverted indexing for feedback and expansion. In: Proceedings of CIKM 2010, pp. 1049–1058 (2010)
Qi, X., Davison, B.D.: Web page classification: Features and algorithms. ACM Comput. Surv. 41(2), 12:1–12:31 (2009)
Yang, Y., Bansal, N., Dakka, W., Ipeirotis, P., Koudas, N., Papadias, D.: Query by document. In: Proceedings of WSDM 2009, pp. 34–43 (2009)
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Hagen, M., Glimm, C. (2014). Supporting More-Like-This Information Needs: Finding Similar Web Content in Different Scenarios. In: Kanoulas, E., et al. Information Access Evaluation. Multilinguality, Multimodality, and Interaction. CLEF 2014. Lecture Notes in Computer Science, vol 8685. Springer, Cham. https://doi.org/10.1007/978-3-319-11382-1_6
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DOI: https://doi.org/10.1007/978-3-319-11382-1_6
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