Our research challenge is to provide a mechanism for splitting into user task-based sessions a long-term log of queries submitted to a Web Search Engine (WSE). The hypothesis is that some query sessions entail the concept of user task. We present an approach that relies on a centroid-based and a density-based clustering algorithm, which consider queries inter-arrival times and use a novel distance function that takes care of query lexical content and exploits the collaborative knowledge collected by Wiktionary and Wikipedia.
Detecting task-based query sessions using collaborative knowledge / Lucchese, C.; Orlando, S.; Perego, R.; Silvestri, F.; Tolomei, G.. - (2010), pp. 128-131. (Intervento presentato al convegno 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) tenutosi a Toronto, ON; Canada) [10.1109/WI-IAT.2010.281].
Detecting task-based query sessions using collaborative knowledge
F. Silvestri;G. Tolomei
2010
Abstract
Our research challenge is to provide a mechanism for splitting into user task-based sessions a long-term log of queries submitted to a Web Search Engine (WSE). The hypothesis is that some query sessions entail the concept of user task. We present an approach that relies on a centroid-based and a density-based clustering algorithm, which consider queries inter-arrival times and use a novel distance function that takes care of query lexical content and exploits the collaborative knowledge collected by Wiktionary and Wikipedia.File | Dimensione | Formato | |
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