Oscar Valdivia

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In this paper we address the issue of continuous keyword queries on multiple textual streams. This line of work represents a significant departure from previous keyword search models that assumed a static database. In our model the user poses a query comprised by a collection of keywords, which is subsequently applied on multiple text streams (these can be(More)
An increasing amount of data is produced in the form of text streams − these can be RSS news feeds, TV closed captions, emails, etc. We study the problem of answering keyword queries on multiple textual streams. We define the result of a keyword query inspired by previous work on keyword search on static databases. A result to a query is a combination of(More)
In this paper we address the issue of continuous keyword queries on multiple textual streams and explore techniques for extracting useful information from them. The paper represents, to our best knowledge, the first approach that performs keyword search on a multiplicity of textual streams. The scenario that we consider is quite intuitive; let's assume that(More)
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