Predicting the effectiveness of queries and retrieval systems

Titel	Predicting the effectiveness of queries and retrieval systems
Auteur	Hauff, Claudia
Promotors	Jong, de F.M.G.; Hiemstra, D.
Universiteit	Universiteit Twente
Datum	2010-01-29
Samenvatting	In this thesis we consider users’ attempts to express their information needs through queries, or search requests and try to predict whether those requests will be of high or low quality. Intuitively, a query’s quality is determined by the outcome of the query, that is, whether the retrieved search results meet the user’s expectations. The second type of prediction methods under investigation are those which attempt to predict the quality of search systems themselves. Given a number of search systems to consider, these methods estimate how well or how poorly the systems will perform in comparison to each other. The motivation for this research effort stems primarily from the enormous benefits originating from successfully predicting the quality of a query or a system. Accurate predictions enable the employment of adaptive retrieval components which would have a considerable positive effect on the user experience. Furthermore, if we would achieve sufficiently accurate predictions of the quality of retrieval systems, the cost of evaluation would be significantly reduced.
Type	proefschrift
Persistent IdentifierDe Persistent Identifiers (PI) is een nummer dat toegekend wordt aan een digitaal object (bijvoorbeeld een publicatie of dataset). Door gebruik te maken van speciale software, kan met behulp van dit nummer (de Uniform Resource Name (URN)) de vindplaats van het object worden terug gevonden, ook al wijzigt de URL waar de publicatie zich bevindt.	URN:NBN:NL:UI:28-69679
Uitgever	University of Twente
Publicatie	http://purl.org/utwente/69679
Metadata	XML
Export	(download Zotero)
Repository	Universiteit Twente