Learning block importance models for web pages

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

ViDE: A Vision-Based Approach for Deep Web Data Extraction (2010, methodology): “To our best knowledge, although there are already some works [3], [4], [23], [26], [28] that pay attention to the visual information on Web pages, our work is the first to perform deep Web data extraction using primarily visual features.”
Introduction to the special topic section on mining Web resources for enhancing information retrieval (2007, methodology): “After a Web page is partitioned into several blocks, algorithms based on learning mechanisms ( Song, Liu, Wen, & Ma, 2004 ) or based on hyperlink structure (Cai, He, Wen, & Ma, 2004) can be performed to locate the important blocks or cleanse the unimportant ones.”
Zero-shot Entity Extraction from Web Pages (2014, unknown): “(Liu et al., 2003; Song et al., 2004; Zhu et al., 2005; Zheng et al., 2007).”
Object-level ranking: bringing order to Web objects (2005, methodology): “Since the information about an object is normally represented as a block of a Web page [12, 14].”
Web data extraction based on partial tree alignment (2005, unknown): “, finding different semantics blocks [29, 28].”