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Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004)
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- Content
- Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
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- 8. 1.2013 10:22:32
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Becks, D.; Schulz, J.M.: Domänenübergreifende Phrasenextraktion mithilfe einer lexikonunabhängigen Analysekomponente (2010)
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- Information und Wissen: global, sozial und frei? Proceedings des 12. Internationalen Symposiums für Informationswissenschaft (ISI 2011) ; Hildesheim, 9. - 11. März 2011. Hrsg.: J. Griesbaum, T. Mandl u. C. Womser-Hacker
-
Strube, M.: Kreativ durch Analogien (2011)
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- Spektrum der Wissenschaft. 2011, H.12, S.30-33
- Year
- 2011
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Vasalou, A.; Gill, A.J.; Mazanderani, F.; Papoutsi, C.; Joinson, A.: Privacy dictionary : a new resource for the automated content analysis of privacy (2011)
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- Journal of the American Society for Information Science and Technology. 62(2011) no.11, S.2095-2105
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- 2011
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Anizi, M.; Dichy, J.: Improving information retrieval in Arabic through a multi-agent approach and a rich lexical resource (2011)
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- Content
- Beitrag innerhalb einer Special Section: Knowledge Organization, Competitive Intelligence, and Information Systems - Papers from 4th International Conference on "Information Systems & Economic Intelligence," February 17-19th, 2011. Marrakech - Morocco.
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- Knowledge organization. 38(2011) no.5, S.405-413
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- 2011
-
Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
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- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
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Warner, A.J.: Natural language processing (1987)
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- Annual review of information science and technology. 22(1987), S.79-108
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Manning, C.D.: Part-of-Speech Tagging from 97% to 100% : is it time for some linguistics? (2011)
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- Source
- Computational Linguistics and Intelligent Text Processing, 12th International Conference, CICLing 2011, Proceedings, Part I. Ed.: Alexander Gelbukh
- Year
- 2011
-
Wong, W.; Liu, W.; Bennamoun, M.: Ontology learning from text : a look back and into the future (2010)
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- Content
- Pre-publication version für: ACM Computing Surveys, Vol. X, No. X, Article X, Publication date: X 2011.
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Stoykova, V.; Petkova, E.: Automatic extraction of mathematical terms for precalculus (2012)
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- Beitrag für: First World Conference on Innovation and Computer Sciences (INSODE 2011). Vgl.: http://www.sciencedirect.com/science/article/pii/S221201731200103X.
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McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996)
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- Computational linguistics. 22(1996) no.2, S.217-248
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Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991)
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- Date
- 8.10.2000 11:52:22
-
Somers, H.: Example-based machine translation : Review article (1999)
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- Date
- 31. 7.1996 9:22:19
-
New tools for human translators (1997)
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- Date
- 31. 7.1996 9:22:19
-
Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997)
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- 28. 2.1999 10:48:22
-
¬Der Student aus dem Computer (2023)
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- Date
- 27. 1.2023 16:22:55
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Byrne, C.C.; McCracken, S.A.: ¬An adaptive thesaurus employing semantic distance, relational inheritance and nominal compound interpretation for linguistic support of information retrieval (1999)
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- Date
- 15. 3.2000 10:22:37
-
Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009)
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- Date
- 1. 3.2013 14:56:22
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Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000)
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- Source
- c't. 2000, H.22, S.230-231
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Chen, L.; Fang, H.: ¬An automatic method for ex-tracting innovative ideas based on the Scopus® database (2019)
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- Abstract
- The novelty of knowledge claims in a research paper can be considered an evaluation criterion for papers to supplement citations. To provide a foundation for research evaluation from the perspective of innovativeness, we propose an automatic approach for extracting innovative ideas from the abstracts of technology and engineering papers. The approach extracts N-grams as candidates based on part-of-speech tagging and determines whether they are novel by checking the Scopus® database to determine whether they had ever been presented previously. Moreover, we discussed the distributions of innovative ideas in different abstract structures. To improve the performance by excluding noisy N-grams, a list of stopwords and a list of research description characteristics were developed. We selected abstracts of articles published from 2011 to 2017 with the topic of semantic analysis as the experimental texts. Excluding noisy N-grams, considering the distribution of innovative ideas in abstracts, and suitably combining N-grams can effectively improve the performance of automatic innovative idea extraction. Unlike co-word and co-citation analysis, innovative-idea extraction aims to identify the differences in a paper from all previously published papers.