Supporting contextualized information finding with automatic excerpt categorization

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Kawase, R.; Siehndel, P.; Nunes, B.P.: Supporting contextualized information finding with automatic excerpt categorization. In: Procedia Computer Science 35 (2014), Nr. C, S. 551-559. DOI: https://doi.org/10.1016/j.procs.2014.08.136

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/906

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Sum total of downloads: 433




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Abstract: 
The volume of information on the Web is constantly growing. Consequently, finding specific pieces of information becomes a harder task. Wikipedia, the largest online reference Website is beginning to witness this phenomenon. Learners often turn to Wikipedia in order to learn facts regarding different subjects. However, as time passes, Wikipedia articles get larger and specific information gets more difficult to be located. In this work, we propose an automatic annotation method that is able to precisely assign categories to any textual resource. Our approach relies on semantic enhanced annotations and the categorization schema of Wikipedia. The results of a user study show that our proposed method provides solid results for classifying text and provides a useful support for locating information. As implication, our research will help future learners to easily identify desired learning topics of interest in large textual resources.
License of this version: CC BY-NC-ND 3.0
Document Type: article
Publishing status: publishedVersion
Issue Date: 2014
Appears in Collections:Fakultät für Elektrotechnik und Informatik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 125 28.87%
2 image of flag of United States United States 120 27.71%
3 image of flag of Indonesia Indonesia 23 5.31%
4 image of flag of Tunisia Tunisia 15 3.46%
5 image of flag of Russian Federation Russian Federation 15 3.46%
6 image of flag of Netherlands Netherlands 15 3.46%
7 image of flag of No geo information available No geo information available 14 3.23%
8 image of flag of France France 13 3.00%
9 image of flag of United Kingdom United Kingdom 10 2.31%
10 image of flag of Latvia Latvia 9 2.08%
    other countries 74 17.09%

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