Elements of information theory
Elements of information theory
A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Temporal summaries of new topics
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The Journal of Machine Learning Research
Text classification and named entities for new event detection
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A graph-theoretic approach to extract storylines from search results
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A cross-collection mixture model for comparative text mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Tracking dynamics of topic trends using a finite mixture model
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A probabilistic model for retrospective news event detection
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
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
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
Time-dependent event hierarchy construction
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic detection by topic model induced distance using biased initiation
AST/UCMA/ISA/ACN'10 Proceedings of the 2010 international conference on Advances in computer science and information technology
DVD: a model for event diversified versions discovery
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Mining event temporal boundaries from news corpora through evolution phase discovery
WAIM'11 Proceedings of the 12th international conference on Web-age information management
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Some recent topic model-based methods have been proposed to discover and summarize the evolutionary patterns of themes in temporal text collections. However, the theme patterns extracted by these methods are hard to interpret and evaluate. To produce a more descriptive representation of the theme pattern, we not only give new representations of sentences and themes with named entities, but we also propose a sentence-level probabilistic model based on the new representation pattern. Compared with other topic model methods, our approach not only gets each topic's distribution per term, but also generates candidate summary sentences of the themes as well. Consequently, the results are easier to understand and can be evaluated using the top sentences produced by our probabilistic model. Experimentation with the proposed methods on the Tsunami dataset shows that the proposed methods are useful in the discovery of evolutionary theme patterns.