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A Connectionist Corpus-Based Approach to the Building of Word Representations (1994)
Rupert L. Tang
A system for building distributed representations for words using a sliding window is described here which takes a corpora of sentences from either artificial data or natural data. The system is able to develop representations that capture the regularity of word occurrences underlying a given body of text. The paradigm presented here is based on a FGREP module with some variations on the architecture and the training methodology. Experiments are done to show that the system is capable of capturing the surface regularity of words.
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Citation:
Technical Report HR-94-01, Department of Computer Science, The University of Texas at Austin.
Bibtex:
@techreport{tang:ugthesis94, title={A Connectionist Corpus-Based Approach to the Building of Word Representations}, author={Rupert L. Tang}, number={HR-94-01}, school={Department of Computer Sciences, The University of Texas at Austin}, institution={Department of Computer Science, The University of Texas at Austin}, type={Undergraduate Honors Thesis}, url="http://www.cs.utexas.edu/users/ai-lab?tang:ugthesis94", year={1994} }
Areas of Interest
Cognitive Science
Concept and Schema Learning
Natural Language Processing (Cognitive)
Software/Data
FGREPNET
The FGREPNET package contains the C-code and data for training and testing an FGREP network in developing distributed re...
1994
Labs
Neural Networks