The information-seeking practices of engineers: searching for documents as well as for people
Information Processing and Management: an International Journal
Stuff I've seen: a system for personal information retrieval and re-use
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Enterprise Search: Tough Stuff
Queue - Search Engines
Challenges in enterprise search
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
TaskTracer: a desktop environment to support multi-tasking knowledge workers
Proceedings of the 10th international conference on Intelligent user interfaces
Evaluating personal information management behaviors and tools
Communications of the ACM - Personal information management
Using annotations in enterprise search
Proceedings of the 15th international conference on World Wide Web
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
CAAD: an automatic task support system
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Towards task-based personal information management evaluations
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Mining the search trails of surfing crowds: identifying relevant websites from user activity
Proceedings of the 17th international conference on World Wide Web
Minimum-effort driven dynamic faceted search in structured databases
Proceedings of the 17th ACM conference on Information and knowledge management
Modeling multi-step relevance propagation for expert finding
Proceedings of the 17th ACM conference on Information and knowledge management
Determining expert profiles (with an application to expert finding)
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Search User Interfaces
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
Retrieval experiments using pseudo-desktop collections
Proceedings of the 18th ACM conference on Information and knowledge management
Beagle++: semantically enhanced searching and ranking on the desktop
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Analyzing user behavior to rank desktop items
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
Facet discovery for structured web search: a query-log mining approach
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Optimizing enterprise search by automatically relating user context to textual document content
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
Building Multi-Modal Relational Graphs for Multimedia Retrieval
International Journal of Multimedia Data Engineering & Management
Relational term-suggestion graphs incorporating multipartite concept and expertise networks
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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With the growing amount of information on users' desktops and increasing scale and complexity of intranets, Enterprise and Desktop Search are becoming two increasingly important Information Retrieval applications. While the challenges arising there are not completely different from those that the web community has faced for years, advanced web search solutions are often unable to address them properly. In this tutorial we give a research prospective on distinctive features of both Enterprise and Desktop Search, explain typical search scenarios, and review existing ranking techniques and algorithms.