A Modified System for Weblog Topic Relevance Retrieval

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原文链接

NETL
IEEE

外文摘要：Weblog is widely used， and the number of users is increasing rapidly。 Weblog reflects every aspect of the society， such as politics， economy and culture， so the topic relevance retrieval research on Weblog becomes necessary。 Because of a lot of noise in the corpus and it is usually difficult to obtain the appropriate query， the common methods sometimes fail to reach an acceptable precision。 We design a Modified Topic Relevance Retrieval System (MTRRS) containing query formulation and a combination model。 To design the query， manual adjustment and machine learning are used。 During the machine learning processing， we define a center word list which helps to generate a novel distance feature。 The result can be improved 22。97% on MAP by query formulation。 The results of document retrieval model and passage retrieval model are combined。 33。55% increase on MAP can be received。 Also by using the combination model， the retrieval result of the semi-machine learning query is closely approaching the manually adjusted result。

外文关键词：

Combination ModelQuery FormulationTopic Relevance Retrieval

作者：

Si Li、Lei Du、Weiran Xu、Jun Guo

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作者单位：

Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China

会议名称：

International Conference on Future Information Technology and Management Engineering;FITME '09

会议地点：

Sanya(CN);Sanya(CN)

会议母体文献：

Future Information Technology and Management Engineering, 2009. FITME '09

页码：

392-395

出版时间：

2009

DOI：

10.1109/FITME.2009.104