Search (29 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Computerlinguistik"
  • × type_ss:"a"
  • × year_i:[2020 TO 2030}
  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.06 
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  2. Morris, V.: Automated language identification of bibliographic resources (2020) 0.03 
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    Date
    2. 3.2020 19:04:22
    Language
    e
  3. Roose, K.: ¬The brilliance and weirdness of ChatGPT (2022) 0.00 
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  4. Metz, C.: ¬The new chatbots could change the world : can you trust them? (2022) 0.00 
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  5. Harari, Y.N.: ¬[Yuval-Noah-Harari-argues-that] AI has hacked the operating system of human civilisation (2023) 0.00 
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  6. Zaitseva, E.M.: Developing linguistic tools of thematic search in library information systems (2023) 0.00 
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    Abstract
    Within the R&D program "Information support of research by scientists and specialists on the basis of RNPLS&T Open Archive - the system of scientific knowledge aggregation", the RNPLS&T analyzes the use of linguistic tools of thematic search in the modern library information systems and the prospects for their development. The author defines the key common characteristics of e-catalogs of the largest Russian libraries revealed at the first stage of the analysis. Based on the specified common characteristics and detailed comparison analysis, the author outlines and substantiates the vectors for enhancing search inter faces of e-catalogs. The focus is made on linguistic tools of thematic search in library information systems; the key vectors are suggested: use of thematic search at different search levels with the clear-cut level differentiation; use of combined functionality within thematic search system; implementation of classification search in all e-catalogs; hierarchical representation of classifications; use of the matching systems for classification information retrieval languages, and in the long term classification and verbal information retrieval languages, and various verbal information retrieval languages. The author formulates practical recommendations to improve thematic search in library information systems.
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  7. Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022) 0.00 
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  8. Xiang, R.; Chersoni, E.; Lu, Q.; Huang, C.-R.; Li, W.; Long, Y.: Lexical data augmentation for sentiment analysis (2021) 0.00 
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  9. Laparra, E.; Binford-Walsh, A.; Emerson, K.; Miller, M.L.; López-Hoffman, L.; Currim, F.; Bethard, S.: Addressing structural hurdles for metadata extraction from environmental impact statements (2023) 0.00 
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  10. Al-Khatib, K.; Ghosa, T.; Hou, Y.; Waard, A. de; Freitag, D.: Argument mining for scholarly document processing : taking stock and looking ahead (2021) 0.00 
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  11. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.00 
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  12. Chou, C.; Chu, T.: ¬An analysis of BERT (NLP) for assisted subject indexing for Project Gutenberg (2022) 0.00 
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  13. Hausser, R.: Grammatical disambiguation : the linear complexity hypothesis for natural language (2020) 0.00 
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  14. Corbara, S.; Moreo, A.; Sebastiani, F.: Syllabic quantity patterns as rhythmic features for Latin authorship attribution (2023) 0.00 
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  15. Shree, P.: ¬The journey of Open AI GPT models (2020) 0.00 
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  16. Lund, B.D.; Wang, T.; Mannuru, N.R.; Nie, B.; Shimray, S.; Wang, Z.: ChatGPT and a new academic reality : artificial Intelligence-written research papers and the ethics of the large language models in scholarly publishing (2023) 0.00 
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  17. Meng, K.; Ba, Z.; Ma, Y.; Li, G.: ¬A network coupling approach to detecting hierarchical linkages between science and technology (2024) 0.00 
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  18. Brown, T.B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; Amodei, D.: Language models are few-shot learners (2020) 0.00 
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  19. Zhang, Y.; Zhang, C.; Li, J.: Joint modeling of characters, words, and conversation contexts for microblog keyphrase extraction (2020) 0.00 
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  20. Escolano, C.; Costa-Jussà, M.R.; Fonollosa, J.A.: From bilingual to multilingual neural-based machine translation by incremental training (2021) 0.00 
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