Passage-level evidence in document retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic text decomposition using text segments and text themes
Proceedings of the the seventh ACM conference on Hypertext
The indexing and retrieval of document images: a survey
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
Modern Information Retrieval
Using Character Shape Coding for Information Retrieval
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Retrieval methods for English-text with missrecognized OCR characters
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Experimental Evaluation of Passage-Based Document Retrieval
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Graphics Recognition - from Re-engineering to Retrieval
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Document Image Retrieval Based on 2D Density Distributions of Terms with Pseudo Relevance Feedback
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Efficient word retrieval by means of SOM clustering and PCA
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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This paper presents a new method of document image retrieval that is capable of spotting parts of page images relevant to a user's query. This enables us to improve the usability of retrieval, since a user can find where to read on retrieved pages. The effectiveness of retrieval can also be improved because the method is little influenced by irrelevant parts on pages. The method is based on the assumption that parts of page images which densely contain keywords in a query are relevant to it. The characteristics of the proposed method are as follows: (1) Two-dimensional density distributions of keywords are calculated for ranking parts of page images, (2) The method relies only on the distribution of characters so as not to be affected by the errors of layout analysis. Based on the experimental results of retrieving Japanese newspaper articles, we have shown that the proposed method is superior to a method without the function of dealing with parts, and sometimes equivalent to a method of electronic document retrieval that works on error-free text.