Accordion summarization for end-game browsing on PDAs and cellular phones
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Function-based object model towards website adaptation
Proceedings of the 10th international conference on World Wide Web
Toward Learning Based Web Query Processing
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Discovering informative content blocks from Web documents
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting content structure for web pages based on visual representation
APWeb'03 Proceedings of the 5th Asia-Pacific web conference on Web technologies and applications
SEA: Segment-enrich-annotate paradigm for adapting dialog-based content for improved accessibility
ACM Transactions on Information Systems (TOIS)
Refining search results using a mining framework
Expert Systems with Applications: An International Journal
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This paper presents experiments using an algorithm of web page topic segmentation that show significant precision improvement in the retrieval of documents issued from the Web track corpus of TREC 2001. Instead of processing the whole document, a web page is segmented into different semantic blocks according to visual criteria (such as horizontal lines, colors) and structural tags (such as headings ~, paragraph ). We conclude that combining visual and content layout criteria gives the best results for increasing the precision: the ranking of the page is calculated for relevant segments of pages resulting from the segmentation algorithm.