Conference proceeding
SimFusion: measuring similarity using unified relationship matrix
Proceedings of the 28th annual international ACM SIGIR conference on research and development in information retrieval, pp.130-137
SIGIR '05
08/15/2005
DOI: 10.1145/1076034.1076059
Abstract
In this paper we use a Unified Relationship Matrix ( URM ) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks, user click-through sequences). We claim that iterative computations over the URM can help overcome the data sparseness problem and detect latent relationships among heterogeneous data objects, thus, can improve the quality of information applications that require com- bination of information from heterogeneous sources. To support our claim, we present a unified similarity-calculating algorithm, SimFusion . By iteratively computing over the URM, SimFusion can effectively integrate relationships from heterogeneous sources when measuring the similarity of two data objects. Experiments based on a web search engine query log and a web page collection demonstrate that SimFusion can improve similarity measurement of web objects over both traditional content based algorithms and the cutting edge SimRank algorithm.
Details
- Title: Subtitle
- SimFusion: measuring similarity using unified relationship matrix
- Creators
- Wensi Xi - Virginia TechEdward Fox - Virginia TechWeiguo Fan - Virginia TechBenyu Zhang - Microsoft Research AsiaZheng Chen - Microsoft Research AsiaJun Yan - Beijing Univ., Beijing, , ChinaDong Zhuang - Beijing Institute of Technology
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 28th annual international ACM SIGIR conference on research and development in information retrieval, pp.130-137
- Publisher
- ACM
- Series
- SIGIR '05
- DOI
- 10.1145/1076034.1076059
- Language
- English
- Date published
- 08/15/2005
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380501502771
Metrics
5 Record Views