A vector space model for automatic indexing
Communications of the ACM
Relationship-based clustering and cluster ensembles for high-dimensional data mining
Relationship-based clustering and cluster ensembles for high-dimensional data mining
Csurf: a context-driven non-visual web-browser
Proceedings of the 16th international conference on World Wide Web
Robust web page segmentation for mobile terminal using content-distances and page layout information
Proceedings of the 16th international conference on World Wide Web
A General Approach for Partitioning Web Page Content Based on Geometric and Style Information
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
A graph-theoretic approach to webpage segmentation
Proceedings of the 17th international conference on World Wide Web
Introduction to Information Retrieval
Introduction to Information Retrieval
Hearsay: a new generation context-driven multi-modal assistive web browser
Proceedings of the 19th international conference on World wide web
Tightly coupling visual and linguistic features for enriching audio-based web browsing experience
Proceedings of the 20th ACM international conference on Information and knowledge management
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People with visual disabilities, especially those who are blind, have digital content narrated to them by text-to-speech (TTS) engines (e.g., with the help of screen readers). Naively narrating web pages, particularly the ones consisting of several diverse pieces (e.g., news summaries, opinion pieces, taxonomy, ads), with TTS engines without organizing them into thematic segments will make it very difficult for the blind user to mentally separate out and comprehend the essential elements in a segment, and the effort to do so can cause significant cognitive stress. One can alleviate this difficulty by segmenting web pages into thematic pieces and then narrating each of them separately. Extant segmentation methods typically segment web pages using visual and structural cues. The use of such cues without taking into account the semantics of the content, tends to produce "impure" segments containing extraneous material interspersed with the essential elements. In this paper, we describe a new technique for identifying thematic segments by tightly coupling visual, structural, and linguistic features present in the content. A notable aspect of the technique is that it produces segments with very little irrelevant content. Another interesting aspect is that the clutter-free main content of a web page, that is produced by the Readability tool and the "Reader" feature of the Safari browser, emerges as a special case of the thematic segments created by our technique. We provide experimental evidence of the effectiveness of our technique in reducing clutter. We also describe a user study with 23 blind subjects of its impact on web accessibility.