1 November 1999 Training perceptrons for document search over the World Wide Web
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In this paper we study the problem of searching documents over the world wide web through training perceptrons. We consider that web documents can be represented by vectors of n boolean attributes. A search process can be viewed as a way of classifying documents over the web according to the user's requirements. We design a perceptron training algorithm for the search engine, and give a bound on the number of trails needed to search for any collection of documents represented by a disjunction of the relevant boolean attributes.
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Zhixiang Chen, Zhixiang Chen, Xiannong Meng, Xiannong Meng, Richard K. Fox, Richard K. Fox, Richard H. Fowler, Richard H. Fowler, } "Training perceptrons for document search over the World Wide Web", Proc. SPIE 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, (1 November 1999); doi: 10.1117/12.367706; https://doi.org/10.1117/12.367706

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