Modern Information Retrieval
Paradigms, citations, and maps of science: a personal history
Journal of the American Society for Information Science and Technology
Time line visualization of research fronts
Journal of the American Society for Information Science and Technology
The Journal of Machine Learning Research
Similarity measures, author cocitation analysis, and information theory: Brief Communication
Journal of the American Society for Information Science and Technology
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
ICML '06 Proceedings of the 23rd international conference on Machine learning
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Topics over time: a non-Markov continuous-time model of topical trends
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A mixture model for contextual text mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic evolution and social interactions: how authors effect research
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Topic sentiment mixture: modeling facets and opinions in weblogs
Proceedings of the 16th international conference on World Wide Web
Anticipating annotations and emerging trends in biomedical literature
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis
Journal of the American Society for Information Science and Technology
Constrained LDA for grouping product features in opinion mining
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
An unsupervised topic segmentation model incorporating word order
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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This paper describes the application of co-occurrence and latent Dirichlet allocation (LDA)-based topic analyses in stem cell-related literature research. On account of the deficiency of parameter estimation in LDA, this study integrated co-occurrence theory and clustering judgement indicators and constructed an ATNLDA (Auto Topic Number LDA) model for topic segmentation. Next, ATNLDA was used to determine the optimal topic number of stem cell research literatures from 2006 to 2011 in PubMed, which was then used for topic segmentation of research content in stem cell data set. After stem cell research topics were obtained, they were analysed in terms of topic label, topic research content and interrelation between topics. The results verified that application of ATNLDA in topic segmentation in stem cell literature research is effective and feasible. Current deficiencies of ATNLDA and future study plan were also discussed.