A citation-based document retrieval system for finding research expertise

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摘要

Current citation-based document retrieval systems generally offer only limited search facilities, such as author search. In order to facilitate more advanced search functions, we have developed a significantly improved system that employs two novel techniques: Context-based Cluster Analysis (CCA) and Context-based Ontology Generation frAmework (COGA). CCA aims to extract relevant information from clusters originally obtained from disparate clustering methods by building relationships between them. The built relationships are then represented as formal context using the Formal Concept Analysis (FCA) technique. COGA aims to generate ontology from clusters relationship built by CCA. By combining these two techniques, we are able to perform ontology learning from a citation database using clustering results. We have implemented the improved system and have demonstrated its use for finding research domain expertise. We have also conducted performance evaluation on the system and the results are encouraging.

论文关键词:Clustering,Indexing,Data mining,Information retrieval,Knowledge discovery,Ontology generation

论文评审过程:Received 24 April 2006, Revised 22 May 2006, Accepted 23 May 2006, Available online 17 July 2006.

论文官网地址:https://doi.org/10.1016/j.ipm.2006.05.015