Automatic metadata generation using associative networks
ACM Transactions on Information Systems (TOIS)
Web-based citation parsing, correction and augmentation
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
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Given the large heterogeneity of the World Wide Web, using metadata on the search engines side seems to be a useful track for information retrieval. Though, because a manual qualification at the Web scale is not accessible, this track is little followed. We propose a semi-automatic method for propagating metadata. In a first step, homegeneous corpus are extracted. We used in our study the following properties: the authority type, the site type, the information type, and the page type. This first step is realized by a clusterization which uses a similarity measure based on the co-citation frequency between pages. Given the cluster hierarchy, the second step selects a reduced number of documents to be manually qualified and propagates the given metadata values to the other documents belonging to the same cluster. A qualitative evaluation and a preliminary study about the scalability of this method are presented.