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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Christiansen, A. Lee, D.J. |
| Copyright Year | 2006 |
| Description | Author affiliation: Brigham Young Univ., Provo, UT (Christiansen, A.; Lee, D.J.) |
| Abstract | This paper addresses relevance feedback as an alternative to keyword-based search engines for sifting through large PDF document collections and extracting the most relevant documents (especially for literature review purposes). Until now, relevance feedback has only been used in content-based image and video retrieval due to the inability to query those media types without keywords. Since PDF journal articles contain many valuable non-keyword features such as structure and formatting information as well as embedded figures, they would benefit from relevance feedback. Stripping a PDF into "full-text" for indexing purposes disregards these important features. We discuss how they can be used to our advantage and look to integrate the wealth of knowledge from relevance feedback text-based information retrieval. We argue for the benefits of placing the burden of relevance judgement on the user rather than the retrieval system and present alternative document views that quickly allow the user to deem relevance |
| Starting Page | 57 |
| Ending Page | 62 |
| File Size | 688534 |
| Page Count | 6 |
| File Format | |
| ISBN | 0769525171 |
| ISSN | 10637125 |
| DOI | 10.1109/CBMS.2006.140 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-06-22 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feedback Search engines Frequency Information retrieval Biomedical imaging Data mining Image retrieval Content based retrieval Indexing Feature extraction |
| Content Type | Text |
| Resource Type | Article |
| Subject | Radiology, Nuclear Medicine and Imaging Computer Science Applications |
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