Searching documentation using text, OCR, and image

ABSTRACT

We describe a mixed-modality method to index and search software documentation in three ways: plain text, OCR text of embedded figures, and visual features of these figures. Using a corpus of 102 computer books with a total of 62,943 pages and 75,800 figures, we empirically demonstrate that our method achieves better precision/recall than do alternatives based on single modalities.

REFERENCES

• 1: Chris Buckley , Ellen M. Voorhees, Retrieval evaluation with incomplete information, Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, July 25-29, 2004, Sheffield, United Kingdom [doi>10.1145/1008992.1009000]
• 2: Josef Sivic , Andrew Zisserman, Video Google: A Text Retrieval Approach to Object Matching in Videos, Proceedings of the Ninth IEEE International Conference on Computer Vision, p.1470, October 13-16, 2003

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms

Keywords:
computer vision, content-based image retrieval, multimodal search