-
Lalmas, M.: XML information retrieval (2009)
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- Source
- Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
-
Martin-Bautista, M.J.; Vila, M.-A.; Larsen, H.L.: ¬A fuzzy genetic algorithm approach to an adaptive information retrieval agent (1999)
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
-
Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014)
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- Date
- 13. 9.2014 14:45:22
-
Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013)
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- Date
- 22. 3.2013 19:34:49
-
Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003)
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- Date
- 11. 9.2004 17:32:22
- Source
- Challenges in knowledge representation and organization for the 21st century: Integration of knowledge across boundaries. Proceedings of the 7th ISKO International Conference Granada, Spain, July 10-13, 2002. Ed.: M. López-Huertas
-
Schamber, L.; Bateman, J.: Relevance criteria uses and importance : progress in development of a measurement scale (1999)
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- Source
- Knowledge: creation, organization and use. Proceedings of the 62nd Annual Meeting of the American Society for Information Science, 31.10.-4.11.1999. Ed.: L. Woods
-
Sakai, T.: On the reliability of information retrieval metrics based on graded relevance (2007)
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- Abstract
- This paper compares 14 information retrieval metrics based on graded relevance, together with 10 traditional metrics based on binary relevance, in terms of stability, sensitivity and resemblance of system rankings. More specifically, we compare these metrics using the Buckley/Voorhees stability method, the Voorhees/Buckley swap method and Kendall's rank correlation, with three data sets comprising test collections and submitted runs from NTCIR. Our experiments show that (Average) Normalised Discounted Cumulative Gain at document cut-off l are the best among the rank-based graded-relevance metrics, provided that l is large. On the other hand, if one requires a recall-based graded-relevance metric that is highly correlated with Average Precision, then Q-measure is the best choice. Moreover, these best graded-relevance metrics are at least as stable and sensitive as Average Precision, and are fairly robust to the choice of gain values.
-
Zhao, L.; Wu, L.; Huang, X.: Using query expansion in graph-based approach for query-focused multi-document summarization (2009)
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-
Longshu, L.; Xia, Z.: On an aproximate fuzzy information retrieval agent (1998)
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-
Wartik, S.; Fox, E.; Heath, L.; Chen, Q.-F.: Hashing algorithms (1992)
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-
Maylein, L.; Langenstein, A.: Neues vom Relevanz-Ranking im HEIDI-Katalog der Universitätsbibliothek Heidelberg : Perspektiven für bibliothekarische Dienstleistungen (2013)
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-
Lee, D.L.; Ren, L.: Document ranking on weight-partitioned signature files (1996)
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-
Boughanem, M.; Chrisment, C.; Tamine, L.: On using genetic algorithms for multimodal relevance optimization in information retrieval (2002)
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