Investigations in Unsupervised Back-of-the-Book Indexing

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This paper discusses investigations in unsupervised back-of-the-book indexing.

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6 p.

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Csomai, Andras & Mihalcea, Rada, 1974- May 2007.


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This paper discusses investigations in unsupervised back-of-the-book indexing.

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6 p.


Abstract: This paper describes our experiments with unsupervised methods for back-of-the-book index construction. Through comparative evaluations performed on a gold standard data set of 29 books and their corresponding indexes, the authors draw conclusions as to what are the most accurate unsupervised methods for automatic index construction. We show that if the right sequence of methods and heuristics is used, the performance of an unsupervised back-of-the-book index construction system can be raised with up to 250% relative increase in F-measure as compared to the performance of a system based on the traditional tf*idf weighting scheme.


  • The Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2007, Key West, Florida, United States


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  • May 2007

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

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  • March 27, 2014, 12:07 p.m.

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Csomai, Andras & Mihalcea, Rada, 1974-. Investigations in Unsupervised Back-of-the-Book Indexing, paper, May 2007; ( accessed March 17, 2018), University of North Texas Libraries, Digital Library,; crediting UNT College of Engineering.