Where should the person stop and the information search interface start?
Information Processing and Management: an International Journal
Statistical methods for speech recognition
Statistical methods for speech recognition
Retrieval effectiveness of surname-title-word searches for known items by academic library users
Journal of the American Society for Information Science
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Encounters with the OPAC: on-line searching in public libraries
Journal of the American Society for Information Science
Searching the Web: the public and their queries
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Combining document representations for known-item search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Language and task independent text categorization with simple language models
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A rich OPAC user interface with AJAX
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Involving users in OPAC interface design: perspective from a UK study
Proceedings of the 2007 conference on Human interface: Part II
User perceptions of online public library catalogues
International Journal of Information Management: The Journal for Information Professionals
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When users seek to find specific resources in a digital library, they often use the library catalog to locate them. These catalog queries are defined as known item queries. As known item queries search for specific resources, it is important to manage them differently from other search types, such as area searches. We study how to identify known item queries in the context of a large academic institution's online public access catalog (OPAC), in which queries are issued via a simple keyword interface. We also examine how to recognize when a known item query has retrieved the item in question. Our approach combines techniques in machine learning, language modeling and machine translation evaluation metrics to build a classifier capable of distinguishing known item queries and correctly classifies titles for whether they are the known item sought with an 80% and 95% correlation to human performance, respectively on each task. To our knowledge, this is the first report of such work, which has the potential to streamline the user interface of both OPACs and digital libraries in support of known item searches.