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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Yongtao Ma Thanh Tran Bicer, V. | 
| Copyright Year | 2013 | 
| Description | Author affiliation: Inst. AIFB, Karlsruhe Inst. of Technol., Karlsruhe, Germany (Yongtao Ma; Thanh Tran) || Smarter Cities Technol. Centre, IBM Res., Dublin, Ireland (Bicer, V.) | 
| Abstract | Structured data representing entity descriptions often lacks precise type information. That is, it is not known to which type an entity belongs to, or the type is too general to be useful. In this work, we propose to deal with this novel problem of inferring the type semantics of structured data, called typification. We formulate it as a clustering problem and discuss the features needed to obtain several solutions based on existing clustering solutions. Because schema features perform best, but are not abundantly available, we propose an approach to automatically derive them from data. Optimized for the use of schema features, we present TYPifier, a novel clustering algorithm that in experiments, yields better typification results than the baseline clustering solutions. | 
| Sponsorship | IEEE Comput. Soc. | 
| Starting Page | 206 | 
| Ending Page | 217 | 
| File Size | 590230 | 
| Page Count | 12 | 
| File Format | |
| ISBN | 9781467349093 | 
| ISSN | 10636382 | 
| e-ISBN | 9781467349109 | 
| e-ISBN | 9781467349086 | 
| DOI | 10.1109/ICDE.2013.6544826 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 2013-04-08 | 
| Publisher Place | Australia | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Semantics Clustering algorithms Resource description framework Feature extraction Measurement Media DVD | 
| Content Type | Text | 
| Resource Type | Article | 
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