A bibliometric system which really works
Journal of the American Society for Information Science
CiteSeer: an automatic citation indexing system
Proceedings of the third ACM conference on Digital libraries
Automating the Construction of Internet Portals with Machine Learning
Information Retrieval
LVis - Digital Library Visualizer
IV '00 Proceedings of the International Conference on Information Visualisation
The Journal of Machine Learning Research
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Identifying a better measure of relatedness for mapping science
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Information extraction from research papers using conditional random fields
Information Processing and Management: an International Journal
Topic and role discovery in social networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Mining for proposal reviewers: lessons learned at the national science foundation
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining a digital library for influential authors
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Measuring conference quality by mining program committee characteristics
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Toward alternative measures for ranking venues: a case of database research community
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Subject metadata enrichment using statistical topic models
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Unsupervised prediction of citation influences
Proceedings of the 24th international conference on Machine learning
Detecting research topics via the correlation between graphs and texts
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Information genealogy: uncovering the flow of ideas in non-hyperlinked document databases
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Studying the history of ideas using topic models
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Identifying the Original Contribution of a Document via Language Modeling
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Detecting topic evolution in scientific literature: how can citations help?
Proceedings of the 18th ACM conference on Information and knowledge management
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
A Survey of Statistical Network Models
Foundations and Trends® in Machine Learning
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Who should I cite: learning literature search models from citation behavior
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Topic-driven multi-type citation network analysis
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
The web of topics: discovering the topology of topic evolution in a corpus
Proceedings of the 20th international conference on World wide web
Computational & Mathematical Organization Theory
Discovering factions in the computational linguistics community
ACL '12 Proceedings of the ACL-2012 Special Workshop on Rediscovering 50 Years of Discoveries
Exploratory simulation of collective innovative behavior in global participatory science communities
Proceedings of the Winter Simulation Conference
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Measurements of the impact and history of research literature provide a useful complement to scientific digital library collections. Bibliometric indicators have been extensively studied, mostly in the context of journals. However, journal-based metrics poorly capture topical distinctions in fast-moving fields, and are increasingly problematic with the rise of open-access publishing. Recent developments in latent topic models have produced promising results for automatic sub-field discovery. The fine-grained, faceted topics produced by such models provide a clearer view of the topical divisions of a body of research literature and the interactions between those divisions. We demonstrate the usefulness of topic models in measuring impact by applying a new phrase-based topic discovery model to a collection of 300,000 Computer Science publications, collected by the Rexa automatic citation indexing system.