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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kandefer, M. Shapiro, S.C. |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Computer Science and Engineering and National Center for Multisource Information Fusion, State University of New York at Buffalo, 201 Bell Hall, Buffalo, New York 14260 (Kandefer, M.; Shapiro, S.C.) |
| Abstract | A soft-information fusion process produces refined estimates of soft-information, such as natural language messages. Information resulting from a soft-information process can be used to retrieve related, relevant information from background (a-priori) knowledge sources using contextual “cues” contained in those messages, a process we call “Context-Based Information Retrieval (CBIR)”. These retrieval results can be used to aid further understanding, and other fusion operations (e.g., data association). CBIR process performance is dependent on the choice of algorithms and parameters for those algorithms, and it is crucial that these are chosen appropriately for the problem domain the CBIR algorithm is used to aid. In this paper an f-measure evaluation of two spreading activation algorithms and their parameters is given using a soft information fusion process in a counterinsurgency domain. This evaluation takes place in two phases. The first phase executes the algorithms over a range of values in order to determine how those parameters affect the performance of the algorithms, and to set these parameters for future use. The second phase compares the results of these algorithms using the parameter settings learned from the first phase. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 581966 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781457702679 |
| e-ISBN | 9780982443828 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Intl Society of Info Fusion |
| Subject Keyword | Information retrieval Cognition Context Mathematical model Algorithm design and analysis Natural languages Equations context exploitation human-based sensing soft information fusion |
| Content Type | Text |
| Resource Type | Article |
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