Clustering Web Search Results with Maximum Spanning Trees

被引：0

作者：

Di Marco, Antonio ^{[1
]}

Navigli, Roberto ^{[1
]}

机构：

[1] Univ Roma La Sapienza, Dipartimento Informat, I-00198 Rome, Italy

来源：

AI(STAR)IA 2011: ARTIFICIAL INTELLIGENCE AROUND MAN AND BEYOND | 2011年 / 6934卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a novel method for clustering Web search results based on Word Sense Induction. First, we acquire the meanings of a query by means of a graph-based Clustering algorithm that calculates the maximum spanning tree of the co-occurrence graph of the query. Then we cluster the search results based on their semantic similarity to the induced word senses. We show that our approach improves classical search result clustering methods in terms of both clustering quality and degree of diversification.

引用

页码：201 / 212

页数：12

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