Abstract
In this chapter we describe the application of the detection of salient sentences for enhancing relevance ranking in the EERQI search engine as well as for the presentation of document snippets in the results lists. In a proof-of-concept experiment we show that the presence of the query word(s) in the salient sentences detected is an important indicator of the relevance of the article. We have compared the relevance of the articles retrieved with our method with those retrieved by the Lucene search engine as configured for the EERQI content base with the default relevance ranking, which is based on word frequency measures. The results are complementary, which points to the utility of the integration of our tool into Lucene.
This adapts and and extends Sándor and Vorndran (2010).
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References
Manning, C.D., Raghavan, P. & Schütze, H., 2009. Introduction to Information Retrieval. Online edition. Cambridge: Cambridge University Press.
Sándor, Á., Vorndran, A. (2010): Extracting relevant messages from social science research papers for improving relevance of retrieval. Workshop on Natural Language Processing Tools Applied to Discourse Analysis in Psychology, Buenos Aires, Brasil, 10-14 May 2010.
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© 2014 Springer Fachmedien Wiesbaden
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Sándor, Á., Vorndran, A. (2014). Enhancing Relevance Ranking of the EERQI Search Engine. In: Gogolin, I., Åström, F., Hansen, A. (eds) Assessing Quality in European Educational Research. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-05969-9_5
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DOI: https://doi.org/10.1007/978-3-658-05969-9_5
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