Using latent semantic analysis to improve access to textual information
CHI '88 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The automatic identification of stop words
Journal of Information Science
Homer: a pattern discovery support system
Conference Companion on Human Factors in Computing Systems
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
ACM SIGIR Forum
Neural Networks
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
Adaptive information retrieval: machine learning in associative networks (connectionist, free-text, browsing, feedback)
Expanding the public sphere through computer-mediated communication: political discussion about abortion in a usenet newsgroup
Continuous analysis of internet text by artificial neural network
Continuous analysis of internet text by artificial neural network
Context-based question-answering evaluation
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A method of cluster-based indexing of textual data
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
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Many segments of modern society, including marketing, politics, government, activism and public safety, desire the ability to find relationships, thus meaning, in public discourse. This can be accomplished by analyzing communication documents according to their content. The increasing use of the Internet for public dialog has made Internet communication a potentially rich source of data in this regard. This study explores the use of an interactive activation with competition (IAC) artificial neural network (ANN) to find relationships in email texts. A modified fully recurrent IAC network was used to process 69 email messages from two threads in the Open Library/Information Science Education Forum using two variations of the self-organizing phase of network formation. These variations were: (1) with and (2) without a linear decay function applied between sentences to the external activation of nodes. The use of the linear decay function, which could be considered a method for including context, produced three positive effects: the entire network was more differentiated from keywords; the keywords were more highly associated with each other, and; roughly half the number of noise strings were highly associated with keywords.