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Taming Social Tags: Computational Linguistic Analysis of Tags for Images in Museums
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Abstract:
This paper reports on the linguistic analysis of a tag set of nearly 50,000 tags collected as part of the steve.museum project. The tags describe images of objects in museum collections. We present our results on morphological, part of speech and semantic analysis. We demonstrate that deeper tag processing provides valuable information for organizing and categorizing social tags. This promises to improve access to museum objects by leveraging the characteristics of tags and the relationships between them rather than treating them as individual items. At a high level, the paper shows the value of using computational linguistic techniques in interdisciplinary projects with museums and libraries.
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URL: http://hdl.handle.net/1903/11394
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Selecting and Categorizing Textual Descriptions of Images in the Context of an Image Indexer's Toolkit
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Measuring Variability in Sentence Ordering for News Summarization
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CLiMB ToolKit: A Case Study of Iterative Evaluation in a Multidisciplinary Project
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9 |
Lexicalized Well-Founded Grammars: Learnability and Merging ...
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Inducing Constraint-based Grammars from a Small Semantic Treebank
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Columbia’s Newsblaster: New Features and Future Directions
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Klavans, Judith L.; Barzilay, Regina; Nenkova, Ani. - : NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations, 2003
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Combining linguistic and machine learning techniques for email summarization
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GIST-IT: Summarizing Email Using Linguistic Knowledge and Machine
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16 |
Evaluation of computational linguistic techniques for identifying significant topics for browsing applications
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18 |
Evaluation of automatically identified index terms for browsing electronic documents
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19 |
Towards multidocument summarization by reformulation: progress and prospects
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