Vers la conception automatique de filtres d'informations efficaces Towards the Automatic Design of Efficient Custom Filters
msra
摘要
The large amount of financial information released daily by press agencies makes the design of custom information filters, at a low development cost, an important issue. We present a comprehensive methodology for designing an information filter on a prescribed topic with a statistical approach. By using a neural network in conjunction with a search engine, we are able to automate to a large extent the construction of the training set. Since the performance of a filter depends strongly on the relevance of the selected inputs, we describe a method for performing feature selection. The filter is in routine use to filter news releases concerning company shareholding, with a precision and a recall of 90%.
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