In the past, information was stored more or less well-structured in database. Nowadays, a lot of information is presented in unstructured format. The management of and retrieval from such large vast of textual information has been a challenging issue for organizations or individuals. Information extraction is the process of extracting relevant data from semi-structured or unstructured documents and transforming them into structured representations. Many information extraction learning techniques have been proposed. However, they are ineffectiveness on unstructured documents. Thus, in the research, we proposed a new information extraction learning algorithm, called LIEF, that enhancing existing information extraction learning techniques. According to the empirical evaluations on news documents that are unstructured format, the LIEF algorithm proposed showed its capabilities in accuracy rate.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0802101-100356 |
| Date | 02 August 2001 |
| Creators | Pen, Chih-Jen |
| Contributors | Fu-Ren Lin, Sheng-Tun Li, Chih-Ping Wei |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0802101-100356 |
| Rights | unrestricted, Copyright information available at source archive |
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