-
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.
- Date
- 8. 1.2013 10:22:32
-
Yannakoudakis, E.J.; Daraki, J.J.: Lexical clustering and retrieval of bibliographic records (1994)
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- Source
- Information retrieval: new systems and current research. Proceedings of the 15th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Glasgow 1993. Ed.: Ruben Leon
-
Gill, A.J.; Hinrichs-Krapels, S.; Blanke, T.; Grant, J.; Hedges, M.; Tanner, S.: Insight workflow : systematically combining human and computational methods to explore textual data (2017)
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- Abstract
- Analyzing large quantities of real-world textual data has the potential to provide new insights for researchers. However, such data present challenges for both human and computational methods, requiring a diverse range of specialist skills, often shared across a number of individuals. In this paper we use the analysis of a real-world data set as our case study, and use this exploration as a demonstration of our "insight workflow," which we present for use and adaptation by other researchers. The data we use are impact case study documents collected as part of the UK Research Excellence Framework (REF), consisting of 6,679 documents and 6.25 million words; the analysis was commissioned by the Higher Education Funding Council for England (published as report HEFCE 2015). In our exploration and analysis we used a variety of techniques, ranging from keyword in context and frequency information to more sophisticated methods (topic modeling), with these automated techniques providing an empirical point of entry for in-depth and intensive human analysis. We present the 60 topics to demonstrate the output of our methods, and illustrate how the variety of analysis techniques can be combined to provide insights. We note potential limitations and propose future work.
-
Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
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- Source
- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
-
Yang, C.C.; Luk, J.: Automatic generation of English/Chinese thesaurus based on a parallel corpus in laws (2003)
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- Abstract
- The information available in languages other than English in the World Wide Web is increasing significantly. According to a report from Computer Economics in 1999, 54% of Internet users are English speakers ("English Will Dominate Web for Only Three More Years," Computer Economics, July 9, 1999, http://www.computereconomics. com/new4/pr/pr990610.html). However, it is predicted that there will be only 60% increase in Internet users among English speakers verses a 150% growth among nonEnglish speakers for the next five years. By 2005, 57% of Internet users will be non-English speakers. A report by CNN.com in 2000 showed that the number of Internet users in China had been increased from 8.9 million to 16.9 million from January to June in 2000 ("Report: China Internet users double to 17 million," CNN.com, July, 2000, http://cnn.org/2000/TECH/computing/07/27/ china.internet.reut/index.html). According to Nielsen/ NetRatings, there was a dramatic leap from 22.5 millions to 56.6 millions Internet users from 2001 to 2002. China had become the second largest global at-home Internet population in 2002 (US's Internet population was 166 millions) (Robyn Greenspan, "China Pulls Ahead of Japan," Internet.com, April 22, 2002, http://cyberatias.internet.com/big-picture/geographics/article/0,,5911_1013841,00. html). All of the evidences reveal the importance of crosslingual research to satisfy the needs in the near future. Digital library research has been focusing in structural and semantic interoperability in the past. Searching and retrieving objects across variations in protocols, formats and disciplines are widely explored (Schatz, B., & Chen, H. (1999). Digital libraries: technological advances and social impacts. IEEE Computer, Special Issue an Digital Libraries, February, 32(2), 45-50.; Chen, H., Yen, J., & Yang, C.C. (1999). International activities: development of Asian digital libraries. IEEE Computer, Special Issue an Digital Libraries, 32(2), 48-49.). However, research in crossing language boundaries, especially across European languages and Oriental languages, is still in the initial stage. In this proposal, we put our focus an cross-lingual semantic interoperability by developing automatic generation of a cross-lingual thesaurus based an English/Chinese parallel corpus. When the searchers encounter retrieval problems, Professional librarians usually consult the thesaurus to identify other relevant vocabularies. In the problem of searching across language boundaries, a cross-lingual thesaurus, which is generated by co-occurrence analysis and Hopfield network, can be used to generate additional semantically relevant terms that cannot be obtained from dictionary. In particular, the automatically generated cross-lingual thesaurus is able to capture the unknown words that do not exist in a dictionary, such as names of persons, organizations, and events. Due to Hong Kong's unique history background, both English and Chinese are used as official languages in all legal documents. Therefore, English/Chinese cross-lingual information retrieval is critical for applications in courts and the government. In this paper, we develop an automatic thesaurus by the Hopfield network based an a parallel corpus collected from the Web site of the Department of Justice of the Hong Kong Special Administrative Region (HKSAR) Government. Experiments are conducted to measure the precision and recall of the automatic generated English/Chinese thesaurus. The result Shows that such thesaurus is a promising tool to retrieve relevant terms, especially in the language that is not the same as the input term. The direct translation of the input term can also be retrieved in most of the cases.
-
Warner, A.J.: Natural language processing (1987)
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- Source
- Annual review of information science and technology. 22(1987), S.79-108
-
McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996)
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- Source
- Computational linguistics. 22(1996) no.2, S.217-248
-
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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- Date
- 28. 2.1999 10:48:22
-
¬Der Student aus dem Computer (2023)
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- Date
- 27. 1.2023 16:22:55
-
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
-
Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000)
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- Source
- c't. 2000, H.22, S.230-231
-
Bowker, L.; Ciro, J.B.: Machine translation and global research : towards improved machine translation literacy in the scholarly community (2019)
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- Abstract
- In the global research community, English has become the main language of scholarly publishing in many disciplines. At the same time, online machine translation systems have become increasingly easy to access and use. Is this a researcher's match made in heaven, or the road to publication perdition? Here Lynne Bowker and Jairo Buitrago Ciro introduce the concept of machine translation literacy, a new kind of literacy for scholars and librarians in the digital age. For scholars, they explain how machine translation works, how it is (or could be) used for scholarly communication, and how both native and non-native English-speakers can write in a translation-friendly way in order to harness its potential. Native English speakers can continue to write in English, but expand the global reach of their research by making it easier for their peers around the world to access and understand their works, while non-native English speakers can write in their mother tongues, but leverage machine translation technology to help them produce draft publications in English. For academic librarians, the authors provide a framework for supporting researchers in all disciplines as they grapple with producing translation-friendly texts and using machine translation for scholarly communication - a form of support that will only become more important as campuses become increasingly international and as universities continue to strive to excel on the global stage. Machine Translation and Global Research is a must-read for scientists, researchers, students, and librarians eager to maximize the global reach and impact of any form of scholarly work.
-
Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997)
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- Date
- 31. 7.1996 9:22:19
-
Kuhlmann, U.; Monnerjahn, P.: Sprache auf Knopfdruck : Sieben automatische Übersetzungsprogramme im Test (2000)
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- c't. 2000, H.22, S.220-229
-
Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996)
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- Date
- 22. 3.2015 9:37:18
-
Wanner, L.: Lexical choice in text generation and machine translation (1996)
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- Date
- 31. 7.1996 9:22:19
