Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
Information Retrieval with Implicitly Temporal Queries
verfasst von : Jingjing Wang, Shengli Wu
Erschienen in: Intelligent Data Engineering and Automated Learning – IDEAL 2017
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
Abstract
Time is an important factor that needs to be considered in information retrieval. Often queries raised to search engines may have temporal intention, or the search results that the user interests are time-dependent. In this paper, we deal with one type of temporal queries – implicitly temporal queries. Those queries do not contain explicitly temporal expressions, but the user’s information need is related to time. For a given query, we analyze its temporal intention and set up two linear combination models. One of them is based on the language modeling, and the other is based on the metric space model. Both of them consider both aspects of content and time to rank all the documents involved. Experiment results with the dataset that was used in the Temporal Information Access task of NTCIR-11 show that our approaches are effective.