| Publisher | Microsoft | ||
|---|---|---|---|
| Format | 221.8KB PDF | Date added | 30 May 2005 |
| Topics | Knowledge and Data Management, Web Content Management, Data Acquisition - ETL | ||
| Downloads | 261 | ||
The Web contains an abundance of useful semi-structured information about real world objects, and the empirical study shows that strong sequence characteristics exist for Web information about objects of the same type across different Web sites. Conditional Random Fields (CRFs) are the state of the art approaches taking the sequence characteristics to do better labeling. However, as the information on a Web page is two-dimensionally laid out, previous linear-chain CRFs have their limitations for Web information extraction. To better incorporate the two-dimensional neighborhood interactions, this paper presents a two-dimensional CRF model to automatically extract object information from the Web. This paper empirically compare the proposed model with existing linear-chain CRF models for product information extraction and the results show the effectiveness of the model.
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