Exploiting Captions for Web Data Mining by Neil C. Rowe
Rowe, Neil C.
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We survey research on using captions in data mining from the Web. Captions are text that describes some other information (typically, multimedia). Since text is considerably easier to index and manipulate than non-text (being usually smaller and less ambiguous), a good strategy for accessing non-text is to index its captions. However, captions are not often obvious on the Web as there are few standards. So caption references can reside within paragraphs near a media reference, in clickable text or display text for it, on names of media files, in headings or titles on the page, and in explicit references arbitrarily far from the media. We discuss the range of possible syntactic clues (such as HTML tags) and semantic clues (such as meanings of particular words). We discuss how to quantify their strength and combine their information to arrive at a consensus. We then discuss the problem of mapping information in captions to information in media objects. While it is hard, classes of mapping schemes are distinguishable, and segmentation of the media can be matched to a parsing of the caption by constraint-satisfaction methods. Active work is addressing the issue of automatically learning the clues for mapping from examples.
This article is to appear in Web Mining: Applications and Techniques ed. A. Scime, 2004.
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Rowe, Neil C. (Monterey, California. Naval Postgraduate School, 1998-07);We discuss the obstacles to inference of correspondances between objects within photographic images and their counterpart concepts in descriptive captions of those images. This is important for information retrieval of ...
Rowe, Neil C. (Monterey, California. Naval Postgraduate School, 2004-06);The easiest way to index multimedia from ordinary Web pages is to find their captions. However, captions are not used consistently, and retrieval effectiveness for caption-based multimedia browsers is significantly poorer ...
Guglielmo, Eugene J.; Rowe, Neil C. (Monterey, California. Naval Postgraduate School., 1996-07);We describe a prototype intelligent information retrieval system that uses natural-language understanding to efficiently locate captioned data. Multimedia data generally require captions to explain their features and ...