Extracting data records from the web using tag path clustering

Fully automatic methods that extract lists of objects from the Web have been studied extensively. Record extraction, the first step of this object extraction process, identifies a set of Web page segments, each of which represents an individual object (e.g., a product). State-of-the-art methods suffice for simple search, but they often fail to handle more complicated or noisy Web page structures due to a key limitation – their greedy manner of identifying a list of records through pairwise comparison (i.e., similarity match) of consecutive segments. This paper introduces a new method for record extraction that captures a list of objects in a more robust way based on a holistic analysis of a Web page. The method focuses on how a distinct tag path appears repeatedly in the DOM tree of the Web document. Instead of comparing a pair of individual segments, it compares a pair of tag path occurrence patterns (called visual signals) to estimate how likely these two tag paths represent the...

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: Gengxin Miao, Jun'ichi Tatemura, Wang-Pin Hsiung, Arsany Sawires, Louise E. Moser
• Keywords: Record Extraction, Tag Paths, Web Page, WWW 2009