Haystack: per-user information environments
Proceedings of the eighth international conference on Information and knowledge management
Modern Information Retrieval
IEEE Internet Computing
MyLifeBits: fulfilling the Memex vision
Proceedings of the tenth ACM international conference on Multimedia
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
How to make a semantic web browser
Proceedings of the 13th international conference on World Wide Web
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Connections: using context to enhance file search
Proceedings of the twentieth ACM symposium on Operating systems principles
Activity based metadata for semantic desktop search
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
Research on personal dataspace management
Proceedings of the 2nd SIGMOD PhD workshop on Innovative database research
Supporting context-based query in personal DataSpace
Proceedings of the 18th ACM conference on Information and knowledge management
Proceedings of the 19th international conference on World wide web
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Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, are an important step towards more efficient personal information management, yet they offer an incomplete solution. While their indexing functionalities in terms of different file types they are able to cope with are impressive, their ranking capabilities are basic, and rely only on textual retrieval measures, comparable to the first generation of web search engines. In this paper we propose to connect semantically related desktop items by exploiting usage analysis information about sequences of accesses to local resources, as well as about each user’s local resource organization structures. We investigate and evaluate in detail the possibilities to translate this information into a desktop linkage structure, and we propose several algorithms that exploit these newly created links in order to efficiently rank desktop items. Finally, we empirically show that the access based links lead to ranking results comparable with TFxIDF ranking, and significantly surpass TFxIDF when used in combination with it, making them a very valuable source of input to desktop search ranking algorithms.