Foundations of statistical natural language processing
Foundations of statistical natural language processing
Modern Information Retrieval
University of Massachusetts: description of the CIRCUS system as used for MUC-4
MUC4 '92 Proceedings of the 4th conference on Message understanding
Query expansion using term relationships in language models for information retrieval
Proceedings of the 14th ACM international conference on Information and knowledge management
Using Semantic Dependencies to Mine Depressive Symptoms from Consultation Records
IEEE Intelligent Systems
Discovering relations among named entities from large corpora
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Unsupervised learning of field segmentation models for information extraction
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
A semantic approach to IE pattern induction
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
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Negative life events play an important role in triggering depressive episodes. Developing psychiatric services that can automatically identify such events is beneficial for mental health care and prevention. Before these services can be provided, some meaningful semantic patterns, such as , have to be extracted. In this work, we present a text mining framework capable of inducing variable-length semantic patterns from unannotated psychiatry web resources. This framework integrates a cognitive motivated model, Hyperspace Analog to Language (HAL), to represent words as well as combinations of words. Then, a cascaded induction process (CIP) bootstraps with a small set of seed patterns and incorporates relevance feedback to iteratively induce more relevant patterns. The experimental results show that by combining the HAL model and relevance feedback, the CIP can induce semantic patterns from the unannotated web corpora so as to reduce the reliance on annotated corpora.