A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Semantic Web Link Analysis to Discover Social Relationships in Academic Communities
SAINT '05 Proceedings of the The 2005 Symposium on Applications and the Internet
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 15th international conference on World Wide Web
POLYPHONET: An advanced social network extraction system from the Web
Web Semantics: Science, Services and Agents on the World Wide Web
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Flink: Semantic Web technology for the extraction and analysis of social networks
Web Semantics: Science, Services and Agents on the World Wide Web
Social network document ranking
Proceedings of the 10th annual joint conference on Digital libraries
HICSS '11 Proceedings of the 2011 44th Hawaii International Conference on System Sciences
Modeling collaborative knowledge of publishing activities for research recommendation
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
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Selecting a good conference or journal in which to publish a new article is very important to many researchers and scholars. The choice of publication venue is usually based on the author's existing knowledge of publication venues in their research domain or the match of the conference topics with their paper content. They may not be aware of new or other more appropriate conference venues to which their paper could be submitted. A traditional way to recommend a conference to a researcher is by analyzing her paper and comparing it to the topics of different conferences using content-based analysis. However, this approach can make errors due to mismatches caused by ambiguity in text comparisons. In this paper, we present a new approach allowing researchers to automatically find appropriate publication venues for their research paper by exploring author's network of related co-authors and other researchers in the same domain. This work is a part of our social network based recommendation research for research publications venues and interesting hot-topic researches. Experiments with a set of ACM SIG conferences show that our new approach outperforms the content-based approach and provides accurate recommendation. This works also demonstrates the feasibility of our ongoing approach aimed at using social network analysis of researchers and experts in the relevant research domains for a variety of recommendation tasks.