Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Enterprise Search: Tough Stuff
Queue - Search Engines
Automatic summarization of search engine hit lists
RANLPIR '00 Proceedings of the ACL-2000 workshop on Recent advances in natural language processing and information retrieval: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 11
Modeling task-genre relationships for IR in the workplace
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Taxonomies by the numbers: building high-performance taxonomies
Proceedings of the 14th ACM international conference on Information and knowledge management
Towards genre classification for IR in the workplace
IIiX Proceedings of the 1st international conference on Information interaction in context
Secure search in enterprise webs: tradeoffs in efficient implementation for document level security
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Navigating the intranet with high precision
Proceedings of the 16th international conference on World Wide Web
Query relaxation using malleable schemas
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Leveraging semantic technologies for enterprise search
Proceedings of the ACM first Ph.D. workshop in CIKM
Graph-based concept identification and disambiguation for enterprise search
Proceedings of the 19th international conference on World wide web
Automatic suggestion of query-rewrite rules for enterprise search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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Unstructured information represents the vast majority of data collected and accessible to enterprises. Exploiting this information requires systems for managing and extracting knowledge from large collections of unstructured data and applications for discovering patterns and relationships. This paper elucidates the differences between search systems for the Web and those for enterprises, with an emphasis on the future of enterprise search systems. It also introduces the Unstructured Information Management Architecture (UIMA) and provides the context for the unstructured information management (UIM) papers that follow.