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|Title:||Stylistic and lexical co-training for Web block classification||Authors:||Lee, C.H.
Lexical and stylistic learners
Web page block classification
Web page division
|Issue Date:||2004||Citation:||Lee, C.H.,Kan, M.-Y.,Lai, S. (2004). Stylistic and lexical co-training for Web block classification. Proceedings of the Interntational Workshop on Web Information and Data Management : 136-143. ScholarBank@NUS Repository.||Abstract:||Many applications which use web data extract information from a limited number of regions on a web page. As such, web page division into blocks and the subsequent block classification have become a preprocessing step. We introduce PARCELS, an open-source, co-trained approach that performs classification based on separate stylistic and lexical views of the web page. Unlike previous work, PARCELS performs classification on fine-grained blocks. In addition to table-based layout, the system handles real-world pages which feature layout based on divisions and spans as well as stylistic inference for pages using cascaded style sheets. Our evaluation shows that the co-training process results in a reduction of 28.5% in error rate over a single-view classifier and that our approach is comparable to other state-of-the-art systems. Copyright 2004 ACM.||Source Title:||Proceedings of the Interntational Workshop on Web Information and Data Management||URI:||http://scholarbank.nus.edu.sg/handle/10635/41312|
|Appears in Collections:||Staff Publications|
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