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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gollub, T. Volske, M. Hagen, M. Stein, B. |
| Copyright Year | 2014 |
| Description | Author affiliation: Bauhaus-Univ. Weimar, Weimar, Germany (Gollub, T.; Volske, M.; Hagen, M.; Stein, B.) |
| Abstract | This paper presents an unsupervised framework for dynamic, subject-oriented taxonomy composition in digital libraries, which can naturally integrate existing library classification systems. The taxonomy classes in our approach correspond to so-called keyqueries that are run against the digital library's full-text retrieval system. Given a document, a keyquery is a set of few keywords for which the document achieves a high relevance score. Keyqueries can hence be viewed as a general and concise description of the returned retrieval results. The keyquery framework addresses important problems of static classification systems: overlarge classes and overly complex taxonomy structures. If, for instance, a leaf class grows to an indigestible size, keyqueries for the contained documents provide a suitable split mechanism. Since queries are well-known to library users from their daily web search experience, they increase the structural complexity in a transparent way. The paper presents also a strategy for taxonomy-based library exploration. Given a user's information need in the form of library documents, we synthesize a hierarchy of keyqueries that covers this library subset. We manage to solve this difficult set covering problem on-the-fly by combining inverted and reverted indexes along with heuristic search space pruning within a map-reduce application. An empirical evaluation with an ACM collection of scientific papers demonstrates the efficiency and effectiveness of our taxonomy composition framework. |
| Starting Page | 39 |
| Ending Page | 48 |
| File Size | 519321 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781479955695 |
| DOI | 10.1109/JCDL.2014.6970148 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-08 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Big data problem Computational modeling Heuristic algorithms Taxonomy Clustering algorithms Dynamic taxonomy composition Search engines Classification systems Libraries Indexes Keyquery Reverted index |
| Content Type | Text |
| Resource Type | Article |
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