Document Genre Identification

Document genre identification based on image and textual features

We identify the genre(s) of documents based on image features to support indexing, organizing, and searching.

Genre has been used to categorize a variety of art and composition forms, including movies, songs, and literature. While entering query terms is the traditional method of searching for documents, genre can provide a complementary, non-topical means to characterize documents and web pages, and can serve as useful metadata when indexing, organizing, and searching for documents. For example, search results can be grouped by genre, or topical search queries can be augmented by web page genre.

In addition to HTML-based documents on the Web, it is now commonplace to search for and distribute documents in other formats commonly associated with office documents, such as PowerPoint or Word. PDF, which is portable, is even more popular than these document creation formats. However, the genre of PDF documents is often unknown, and document creation programs can be used to create documents in multiple genres.

We have developed a system to identify the genre(s) of documents based on image features. Example genres are shown in the upper figure. The system has been used to tag a corpus for the DocuBrowse system by genre. Results when the genre facet is set to ‘Tech paper’ are shown in the lower figure.

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Related Publications

2012
Publication Details
  • International Journal on Document Analysis and Recognition (IJDAR): Volume 15, Issue 3 (2012), pp. 167-182.
  • Sep 1, 2012

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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 genre identification performance. In the open-set identification of four office document genres, 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 genre identification of office documents. 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.
2010
Publication Details
  • ACM DocEng 2010
  • Sep 21, 2010

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We present a method for picture detection in document page images, which can come from scanned or camera images, or rendered from electronic file formats. Our method uses OCR to separate out the text and applies the Normalized Cuts algorithm to cluster the non-text pixels into picture regions. A refinement step uses the captions found in the OCR text to deduce how many pictures are in a picture region, thereby correcting for under- and over-segmentation. A performance evaluation scheme is applied which takes into account the detection quality and fragmentation quality. We benchmark our method against the ABBYY application on page images from conference papers.

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Browsing and searching for documents in large, online enterprise document repositories are common activities. While internet search produces satisfying results for most user queries, enterprise search has not been as successful because of differences in document types and user requirements. To support users in finding the information they need in their online enterprise repository, we created DocuBrowse, a faceted document browsing and search system. Search results are presented within the user-created document hierarchy, showing only directories and documents matching selected facets and containing text query terms. In addition to file properties such as date and file size, automatically detected document types, or genres, serve as one of the search facets. Highlighting draws the user’s attention to the most promising directories and documents while thumbnail images and automatically identified keyphrases help select appropriate documents. DocuBrowse utilizes document similarities, browsing histories, and recommender system techniques to suggest additional promising documents for the current facet and content filters.
Publication Details
  • Fuji Xerox Technical Report No. 19, pp. 88-100
  • Jan 1, 2010

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Browsing and searching for documents in large, online enterprise document repositories is an increasingly common problem. While users are familiar and usually satisfied with Internet search results for information, enterprise search has not been as successful because of differences in data types and user requirements. To support users in finding the information they need from electronic and scanned documents in their online enterprise repository, we created an automatic detector for genres such as papers, slides, tables, and photos. Several of those genres correspond roughly to file name extensions but are identified automatically using features of the document. This genre identifier plays an important role in our faceted document browsing and search system. The system presents documents in a hierarchy as typically found in enterprise document collections. Documents and directories are filtered to show only documents matching selected facets and containing optional query terms and to highlight promising directories. Thumbnail images and automatically identified keyphrases help select desired documents.