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Logistic Regression and EVIs for XML Books and the Heterogeneous Track

  • Conference paper
Focused Access to XML Documents (INEX 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4862))

Abstract

For this year’s INEX UC Berkeley focused on the Book track and the Heterogeneous track, For these runs we used the TREC2 logistic regression probabilistic model with blind feedback as well as Entry Vocabulary Indexes (EVIs) for the Books Collection MARC data. For the full text records of the book track we encountered a number of interesting problems in setting up the database, and ended up using page-level indexing of the full collection.

As (once again) the only group to actually submit runs for the Het track, we are guaranteed both the highest, and lowest, effectiveness scores for each task. However, because it was again deemed pointless to conduct the actual relevance assessments on the submissions of a single system, we do not know the exact values of these results.

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Authors and Affiliations

  1. School of Information, University of California, Berkeley, Berkeley, California, USA, 94720-4600

    Ray R. Larson

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  1. Ray R. Larson
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Norbert Fuhr Jaap Kamps Mounia Lalmas Andrew Trotman

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Larson, R.R. (2008). Logistic Regression and EVIs for XML Books and the Heterogeneous Track. In: Fuhr, N., Kamps, J., Lalmas, M., Trotman, A. (eds) Focused Access to XML Documents. INEX 2007. Lecture Notes in Computer Science, vol 4862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85902-4_15

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  • DOI: https://doi.org/10.1007/978-3-540-85902-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85901-7

  • Online ISBN: 978-3-540-85902-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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