Searching documentation using text, OCR, and image

Authors:
Tom Yeh;Boris Katz
Affiliations:
MIT, Cambridge, MA, USA;MIT, Cambridge, MA, USA
Venue:
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Year:
2009

Citing 2
Cited 2

Video Google: A Text Retrieval Approach to Object Matching in Videos

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Retrieval evaluation with incomplete information

Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

A case for query by image and text content: searching computer help using screenshots and keywords

Proceedings of the 20th international conference on World wide web
Combining image and text features: a hybrid approach to mobile book spine recognition

MM '11 Proceedings of the 19th ACM international conference on Multimedia

Quantified Score

Hi-index	0.00

Visualization

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.