Mining search-phrase definitions from item descriptions

被引：0

作者：

Nguyen, Hung V. ^{[1
]}

Davulcu, Hasan ^{[1
]}

机构：

[1] Arizona State Univ, Dept Comp Sci & Engn, Tempe, AZ 85287 USA

来源：

2008 IEEE 24TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3 | 2008年

关键词：

D O I：

10.1109/ICDE.2008.4497551

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we develop a model for representing term dependence based on Markov Random Fields and present an approach based on Markov Chain Monte Carlo technique for generating phrase definitions. This approach can use a small corpus of keyword matching and a random sample of other product descriptions for an advertiser's search-phrase to effectively mine and rank alternative but highly relevant search-phrase definitions. These definitions, which are search-phrases themselves, can then be provided as alternative phrases to an advertiser.

引用

页码：1346 / 1348

页数：3

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