Kawase, R.; Siehndel, P.; Nunes, B.P.: Supporting contextualized information finding with automatic excerpt categorization. In: Jędrzejowicz, P.; Czarnowski, I.; Howlett, R.J.; Jain, L.C. (Eds.): Knowledge-Based and Intelligent Information & Engineering Systems 18th Annual Conference, KES-2014. Amsterdam [u.a.] : Elsevier, 2014 (Procedia computer science ; 35), S. 551-559. DOI: https://doi.org/10.1016/j.procs.2014.08.136
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 Unported |
Document Type: | BookPart |
Publishing status: | publishedVersion |
Issue Date: | 2014 |
Appears in Collections: | Fakultät für Elektrotechnik und Informatik |
pos. | country | downloads | ||
---|---|---|---|---|
total | perc. | |||
1 | Germany | 251 | 28.27% | |
2 | United States | 231 | 26.01% | |
3 | No geo information available | 83 | 9.35% | |
4 | Russian Federation | 28 | 3.15% | |
5 | Indonesia | 26 | 2.93% | |
6 | France | 26 | 2.93% | |
7 | Netherlands | 21 | 2.36% | |
8 | United Kingdom | 21 | 2.36% | |
9 | Canada | 21 | 2.36% | |
10 | Tunisia | 15 | 1.69% | |
other countries | 165 | 18.58% |
Hinweis
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