Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Proceedings of the 11th international conference on World Wide Web
Toward a unification of text and link analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Link fusion: a unified link analysis framework for multi-type interrelated data objects
Proceedings of the 13th international conference on World Wide Web
Object-level ranking: bringing order to Web objects
WWW '05 Proceedings of the 14th international conference on World Wide Web
Bibliometric impact measures leveraging topic analysis
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Topical link analysis for web search
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Latent semantic analysis for multiple-type interrelated data objects
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Voting for candidates: adapting data fusion techniques for an expert search task
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Mining a digital library for influential authors
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Co-ranking Authors and Documents in a Heterogeneous Network
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Combining full text and bibliometric information in mapping scientific disciplines
Information Processing and Management: an International Journal - Special issue: Infometrics
Probabilistic models for expert finding
ECIR'07 Proceedings of the 29th European conference on IR research
Award prediction with temporal citation network analysis
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
ICADL'11 Proceedings of the 13th international conference on Asia-pacific digital libraries: for cultural heritage, knowledge dissemination, and future creation
BibRank: a language-based model for co-ranking entities in bibliographic networks
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
New metric measure for the improvement of search results in microblogs
Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics
Academic network analysis: a joint topic modeling approach
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
OverCite: finding overlapping communities in citation network
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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In every scientific field, automated citation analysis enables the estimation of importance or reputation of publications and authors. In this paper, we focus on the task of ranking authors. Although previous work has used content-based approaches or citation network link analyses, the combination of the two with topical link analyses is unexplored. Moreover, previous citation analysis applications are typically limited to a graph based on author citations, or a bipartite graph based on author and paper citations. We present in this paper a novel integrated probabilistic model which combines a content-based approach with a multi-type citation network which integrates citations among papers, authors, affiliations and publishing venues in a single model. We further introduce the application of Topical PageRank into citation network link analysis due to the fact that researchers may be experts in different scientific domains. Finally, we describe a heterogenous link analysis of the citation network, exploring the impact of weighting various factors. Comparative experimental results based on data extracted from the ACM digital library show that 1) the multi-type citation graph works better than citation graphs integrating fewer types of entities, 2) the use of Topical PageRank can further improve performance, and 3) Heterogenous PageRank with parameter tuning can work even better than Topical PageRank.