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Genre identification for office document search and browsing

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Abstract

When searching or browsing documents, the genre of a document is an important consideration that complements topical characterization. We examine design considerations for automatic tagging of office document pages with genre membership. These include selecting features that characterize genre-related information in office documents, examining the utility of text-based features and image-based features, and proposing a simple ensemble method to improve the performance of genre identification. Experiments were conducted on the open-set identification of four coarse office document genres: technical paper, photo, slide, and table. Our experiments show that when combined with image-based features, text-based features do not significantly influence performance. These results provide support for a topic-independent approach to identification of coarse office document genres. Experiments also show that our simple ensemble method significantly improves performance relative to using a support vector machine (SVM) classifier alone. We demonstrate the utility of our approach by integrating our automatic genre tags in a faceted search and browsing application for office document collections.

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Authors and Affiliations

  1. FX Palo Alto Laboratory, Inc., 3400 Hillview Ave, Bldg. 4, Palo Alto, CA, 94304, USA

    Francine Chen, Andreas Girgensohn, Matthew Cooper & Gerry Filby

  2. Texas State University, San Marcos, TX, 78747, USA

    Yijuan Lu

Authors
  1. Francine Chen
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  2. Andreas Girgensohn
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  3. Matthew Cooper
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  4. Yijuan Lu
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  5. Gerry Filby
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Correspondence to Francine Chen.

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Chen, F., Girgensohn, A., Cooper, M. et al. Genre identification for office document search and browsing. IJDAR 15, 167–182 (2012). https://doi.org/10.1007/s10032-011-0163-7

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  • DOI: https://doi.org/10.1007/s10032-011-0163-7

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