Disambiguating Implicit Temporal Queries by Clustering Top Relevant Dates in Web Snippets

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Campos, R (Autor) Outra; Jorge, AM (Autor) FCUP; Dias, G (Autor) Outra; Nunes, C (Autor) Outra

Ata de Conferência Internacional

Título: 2012 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT 2012), VOL 1

Páginas: 1-8

11th IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

Macau, PEOPLES R CHINA, DEC 04-07, 2012

Indexação

ISI Web of Knowledge - 9 Citações

Scopus - 18 Citações

Outras Informações

ID Authenticus: P-008-B7X

DOI: 10.1109/wi-iat.2012.158

Abstract (EN): With the growing popularity of research in Temporal Information Retrieval (T-IR), a large amount of temporal data is ready to be exploited. The ability to exploit this information can be potentially useful for several tasks. For example, when querying "Football World Cup Germany", it would be interesting to have two separate clusters {1974,2006} corresponding to each of the two temporal instances. However, clustering of search results by time is a non-trivial task that involves determining the most relevant dates associated to a query. In this paper, we propose a first approach to flat temporal clustering of search results. We rely on a second order co-occurrence similarity measure approach which first identifies top relevant dates. Documents are grouped at the year level, forming the temporal instances of the query. Experimental tests were performed using real-world text queries. We used several measures for evaluating the performance of the system and compared our approach with Carrot Web-snippet clustering engine. Both experiments were complemented with a user survey.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8