A Document Retrieval Model Based on Digital Signal Filtering

Information retrieval (IR) systems are designed, in general, to satisfy the information need of a user who expresses it by means of a query, by providing him with a subset of documents selected from a collection and ordered by decreasing relevance to the query. Such systems are based on IR models, which define how to represent the documents and the query, as well as how to determine the relevance of a document for a query. In this article, we present a new IR model based on concepts taken from both IR and digital signal processing (like Fourier analysis of signals and filtering). This allows the whole IR process to be seen as a physical phenomenon, where the query corresponds to a signal, the documents correspond to filters, and the determination of the relevant documents to the query is done by filtering that signal. Tests showed that the quality of the results provided by this IR model is comparable with the state-of-the-art.

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