Paper: HAL-Based Cascaded Model For Variable-Length Semantic Pattern Induction From Psychiatry Web Resources

ACL ID P06-2121
Title HAL-Based Cascaded Model For Variable-Length Semantic Pattern Induction From Psychiatry Web Resources
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

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 pre- vention. Before these services can be provided, some meaningful semantic pat- terns, 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) boot- straps with a small set of seed patterns and incorporates relevance feedback to iteratively induce more relevant patterns. The ex...