Daniel Gayo-Avello

  1. On the Fly Query Entity Decomposition Using Snippets.

    Authors: Daniel Gayo-Avello, David J. Brenes, Rodrigo Garcia
    Subjects: Information Retrieval
    Abstract

    One of the most important issues in Information Retrieval is inferring the
    intents underlying users' queries. Thus, any tool to enrich or to better
    contextualized queries can proof extremely valuable. Entity extraction,
    provided it is done fast, can be one of such tools. Such techniques usually
    rely on a prior training phase involving large datasets. That training is
    costly, specially in environments which are increasingly moving towards real
    time scenarios where latency to retrieve fresh informacion should be minimal.
    In this paper an `on-the-fly' query decomposition method is proposed.

  2. Nepotistic Relationships in Twitter and their Impact on Rank Prestige Algorithms.

    Authors: Daniel Gayo-Avello
    Subjects: Information Retrieval
    Abstract

    Micro-blogging services such as Twitter allow anyone to publish anything,
    anytime. Nonetheless to say, many of the available contents can be diminished
    as babble or spam. However, given the number and diversity of users, some
    valuable pieces of information should arise from the stream of tweets. Thus,
    such services can develop into valuable sources of up-to-date information (the
    so-called real-time web) provided a way to find the most
    relevant/trustworthy/authoritative users is available.

  3. Making the road by searching - A search engine based on Swarm Information Foraging.

    Authors: Daniel Gayo-Avello, David J. Brenes
    Subjects: Information Retrieval
    Abstract

    Search engines are nowadays one of the most important entry points for
    Internet users and a central tool to solve most of their information needs.
    Still, there exist a substantial amount of users' searches which obtain
    unsatisfactory results. Needless to say, several lines of research aim to
    increase the relevancy of the results users retrieve. In this paper the authors
    frame this problem within the much broader (and older) one of information
    overload.

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