Advances in Information Retrieval Recent Research from the Center for Intelligent Information Retrieval /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Croft, W. Bruce (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US, 2000.
• Σειρά: The Information Retrieval Series, 7
• Θέματα: Computer science.; Computer communication systems.; Data structures (Computer science).; Information storage and retrieval.; Multimedia information systems.; Computer Science.; Information Storage and Retrieval.; Data Structures, Cryptology and Information Theory.; Computer Communication Networks.; Multimedia Information Systems.

 The Center for Intelligent Information Retrieval (CIIR) was formed in the Computer Science Department ofthe University ofMassachusetts, Amherst in 1992. The core support for the Center came from a National Science Foun- tion State/Industry/University Cooperative Research Center(S/IUCRC) grant, although there had been a sizeable information retrieval (IR) research group for over 10 years prior to that grant. Thebasic goal ofthese Centers is to combine basic research, applied research, and technology transfer. The CIIR has been successful in each of these areas, in that it has produced over 270 research papers, has been involved in many successful government and industry collaborations, and has had a significant role in high-visibility Internet sites and start-ups. As a result of these efforts, the CIIR has become known internationally as one of the leading research groups in the area of information retrieval. The CIIR focuses on research that results in more effective and efficient access and discovery in large, heterogeneous, distributed, text and multimedia databases. The scope of the work that is done in the CIIR is broad and goes significantly beyond “traditional” areas of information retrieval such as retrieval models, cross-lingual search, and automatic query expansion. The research includes both low-level systems issues such as the design of protocols and architectures for distributed search, as well as more human-centered topics such as user interface design, visualization and data mining with text, and multimedia retrieval. 

 Combining Approaches to Information Retrieval -- The use of Exploratory Data Analysis in Information Retrieval Research -- Language Models for Relevance Feedback -- Topic Detection and Tracking: Event Clustering as a Basis for First Story Detection -- Distributed Information Retrieval -- Topic-Based Language Models for Distributed Retrieval -- The Effect of Collection Organization and Query Locality on Information Retrieval System Performance -- Cross-Language Retrieval via Transitive Translation -- Building, Testing, and Applying Concept Hierarchies -- Appearance-Based Global Similarity Retrieval of Images.