Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Result Diversification for Tweet Search
verfasst von : Makbule Gulcin Ozsoy, Kezban Dilek Onal, Ismail Sengor Altingovde
Erschienen in: Web Information Systems Engineering – WISE 2014
Verlag: Springer International Publishing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Being one of the most popular microblogging platforms, Twitter handles more than two billion queries per day. Given the users’ desire for fresh and novel content but their reluctance to submit long and descriptive queries, there is an inevitable need for generating diversified search results to cover different aspects of a query topic. In this paper, we address diversification of results in tweet search by adopting several methods from the text summarization and web search domains. We provide an exhaustive evaluation of all the methods using a standard dataset specifically tailored for this purpose. Our findings reveal that implicit diversification methods are more promising in the current setup, whereas explicit methods need to be augmented with a better representation of query sub-topics.