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Título: UAM at INEX 2012 relevance feedback track: using a probabilistic method for ranking refinement
Autor(es): VILLATORO TELLO, ESAU
SANCHEZ SANCHEZ, CHRISTIAN
JIMENEZ SALAZAR, HECTOR
LUNA RAMIREZ, WULFRANO ARTURO
RODRIGUEZ LUCATERO, CARLOS
Temas: Recuperación de información
Método probabilístico
Refinamiento de clasificación
Fecha: 2012
Editorial: Roma : Initiative for the Evaluation of XML
Citation: INEX’12 Workshop Pre-proceeding
Resumen: This paper describes the system developed by the Language and Reasoning Group of UAM for the Relevance Feedback track of INEX 2012. The presented system focuses on the problem of ranking documents in accordance to their relevance. It is mainly based on the following hypotheses: (i) current IR machines are able to retrieve relevant documents for most of general queries, but they can not generate a pertinent ranking; and (ii) focused relevance feedback could provide more and better elements for the ranking process than isolated query terms. Based on these hypotheses, our participation at INEX 2012 aimed to demonstrate that using some query-related relevance feedback it is possible to improve the final ranking of the retrieved documents.
URI: http://ilitia.cua.uam.mx:8080/jspui/handle/123456789/789
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