Exploiting a Proximity-based Positional Model to Improve the Quality of Information Extraction by Text Segmentation
A large number of web pages contain information of entities in a form of lists of field values. Those implicit semi-structured records are often available in textual sources on the web such as advertisings of products, postal addresses, bibliographic information, etc. Harvesting information of those entities from such lists of field values is challenge task because the lists are manually generated, not written in a well-defined templates or may miss some information. In this paper, the authors introduce a Proximity-based Positional Model (PPM) to improve the quality of extracting information by text segmentation.
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