In this thesis, we have treated the problem of separating content from noise on news websites. We have approached this problem by using TiMBL, a memory-based learning software. We have studied the relevance of the similarity in the training data and the effect of data size in the performance of the extractions.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ntnu-9898 |
Date | January 2009 |
Creators | Arizaleta, Mikel |
Publisher | Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, Institutt for datateknikk og informasjonsvitenskap |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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