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Many pattern recognition tasks can modeled as proximity searching. From nearest neighbor classification to multimedia databases the common task is to quickly find all the elements close to a given query. This task can be accomplished very easily by sequentially examining all the elements in the collection, but turns to be impractical in two situations: when(More)
Proximity searching is the problem of retrieving, from a given database, those objects closest to a query. To avoid exhaustive searching, data structures called indexes are built on the database prior to serving queries. The curse of dimensionality is a well-known problem for indexes: in spaces with sufficiently concentrated distance histograms, no index(More)
Monitoring media broadcast content has deserved a lot of attention lately from both academy and industry due to the technical challenge involved and its economic importance (e.g. in advertising). The problem pose a unique challenge from the pattern recognition point of view because a very high recognition rate is needed under non ideal conditions. The(More)
Remote object management is a key element in distributed and collaborative information retrieval, peer-to-peer systems and agent oriented programming. In existing implementations the communication and parsing overhead represents a significant fraction of the overall latency time in information retrieval tasks. Furthermore, existing architectures are(More)
Recently, sentiment analysis has received a lot of attention due to the interest in mining opinions of social media users. Sentiment analysis consists in determining the polarity of a given text, i.e., its degree of positiveness or negativeness. Traditionally, Sentiment Analysis algorithms have been tailored to a specific language given the complexity of(More)