Items by Tatemura, Junichi
Number of items: 2. Wook Kim, Jong and Selçuk Candan, K. and Tatemura, Junichi Efficient Overlap and Content Reuse Detection in Blogs and Online News Articles. The use of blogs to track and comment on real world (political, news, entertainment) events is growing. Similarly, as more individuals start relying on the Web as their primary information source and as more traditional media outlets try reaching consumers through alternative venues, the number of news sites on the Web is also continuously increasing. Content-reuse, whether in the form of extensive quotations or content borrowing across media outlets, is very common in blogs and news entries outlets tracking the same real-world event. Knowledge about which web entries re-use content from which others can be an effective asset when organizing these entries for presentation. On the other hand, this knowledge is not cheap to acquire: considering the size of the related space web entries, it is essential that the techniques developed for identifying re-use are fast and scalable. Furthermore, the dynamic nature of blog and news entries necessitates incremental processing for reuse detection. In this paper, we develop a novel qSign algorithm that efficiently and effectively analyze the blogosphere for quotation and reuse identification. Experiment results show that with qSign processing time gains from 10X to 100X are possible while maintaining reuse detection rates of upto 90%. Furthermore, processing time gains can be pushed multiple orders of magnitude (from 100X to 1000X) for 70% recall.
Miao, Gengxin and Tatemura, Junichi and Hsiung, Wang-Pin and Sawires, Arsany and Moser, Louise E. 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 same list of objects. The paper introduces a similarity measure that captures how closely the visual signals appear and interleave. Clustering of tag paths is then performed based on this similarity measure, and sets of tag paths that form the structure of data records are extracted. Experiments show that this method achieves higher accuracy than previous methods.
This list was generated on Thu May 23 18:54:01 2013 BST.
About this site
This website has been set up for WWW2009 by Christopher Gutteridge of the University of Southampton, using our EPrints software.
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We (Southampton EPrints Project) intend to preserve the files and HTML pages of this site for many years, however we will turn it into flat files for long term preservation. This means that at some point in the months after the conference the search, metadata-export, JSON interface, OAI etc. will be disabled as we "fossilize" the site. Please plan accordingly. Feel free to ask nicely for us to keep the dynamic site online longer if there's a rally good (or cool) use for it...
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Handy Tools
These are not directly related to the EPrints set up, but may be of use to delegates.
- Social tool links
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