Document representation models for retrieval systems
SIGIR '79 Proceedings of the 2nd annual international ACM SIGIR conference on Information storage and retrieval: information implications into the eighties
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Classification of Web Documents Using a Graph Model
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
An ontology-based method for project and domain expert matching
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Document retrieval using semantic relation in domain ontology
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
A web-based novel term similarity framework for ontology learning
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
An Ontology-Based Approach to Text Summarization
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
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This paper proposes a novel expert peering system for information exchange. Our objective is to develop a real-time search engine for an online community where users can query experts, who are simply other participating users knowledgeable in that area, for help on various topics. We consider a graph-based scheme consisting of an ontology tree where each node represents a (sub)topic. Consequently, the fields of expertise or profiles of the participating experts correspond to subtrees of this ontology. Since user queries can also be mapped to similar tree structures, assigning queries to relevant experts becomes a problem of graph matching. A serialization of the ontology tree allows us to use simple dot products on the ontology vector space effectively to address this problem. As a demonstrative example, we conduct extensive experiments with different parameterizations. We observe that our approach is efficient and yields promising results.