BibTeX
@MISC{_event-centeredinformation,
author = {},
title = {Event-Centered Information Retrieval Using Kernels on Event Graphs},
year = {}
}
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Abstract
Traditional information retrieval models assume keyword-based queries and use unstructured document representations. There is an abundance of event-centered texts (e.g., breaking news) and event-oriented information needs that often involve structure that cannot be expressed using keywords. We present a novel retrieval model that uses a structured event-based representation. We structure queries and documents as graphs of event mentions and employ graph kernels to measure the query-document similarity. Experimental results on two event-oriented test collections show significant improvements over state-ofthe-art keyword-based models. 1
Keyphrases
event-centered information retrieval using kernel event graph structured event-based representation significant improvement traditional information retrieval model event-oriented test collection structure query state-ofthe-art keyword-based model use unstructured document representation event-centered text keyword-based query event mention graph kernel event-oriented information experimental result query-document similarity novel retrieval model
