Carnegie Mellon University
Learning Text Filtering Preferences

Katia Sycara and Anandeep S. Pannu
Symposium on Machine Learning And Information Access, 1996.

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We describe a reusable agent that learns a model of the user's research interests for ltering conference announcements and request for proposals (RFPs) from the Web. For this task, there is a large volume of irrelevant documents and the proportion of relevant documents is very small. It is also critical that the agent not misclassify relevant documents. Information Retrieval and Neural Network techniques were utilized to learn the model of user's preferences. Learning was bootstrapped using papers and proposals the user had written as positive examples. The agent's performance at startup is quite high. Information retrieval and Neural Nets were used to train the agent and experimental performance results were obtained and reported.


Text Reference
Katia Sycara and Anandeep S. Pannu, "Learning Text Filtering Preferences," Symposium on Machine Learning And Information Access, 1996.

BibTeX Reference
   author = "Katia Sycara and Anandeep S. Pannu",
   title = "Learning Text Filtering Preferences",
   booktitle = "Symposium on Machine Learning And Information Access",
   year = "1996",