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Generating AIML rules from Twitter conversations

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Konferencja
Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems
Języki publikacji
EN
Abstrakty
EN
A chat dialogue system or a conversational agent is a computer program designed to hold a conversation using natural language. Many popular chat dialogue systems are based on handcrafted rules, written in Artificial Intelligence Markup Language (AIML). However, manual design of rules requires significant efforts, so certain approaches for automating this process can be helpful. This paper presents some preliminary experiments to generate AIML knowledge automatically using conversation data acquired from Twitter. The experimental results show the possibility of obtaining natural-language conversation between the user and a dialogue system without the necessity of handcrafting its knowledgebase.
Słowa kluczowe
Rocznik
Tom
Strony
59--61
Opis fizyczny
Bibliogr. 9 poz
Twórcy
  • The University of Aizu Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-8580 Japan
  • The University of Aizu Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima, 965-8580 Japan
Bibliografia
  • 1. B. A. Shawar and E. Atwell, “ALICE chatbot: trials and outputs,” Computación y Sistemas, vol. 19, no. 4, pp. 625-632, 2015.
  • 2. R. Higashinaka, K. Imamura, T. Meguro, C. Miyazaki, N. Kobayashi, H. Sugiyama, T. Hirano, T. Makino, and Y. Matsuo, “Towards an open-domain conversational system fully based on natural language processing.,” in COLING, pp. 928-939, 2014.
  • 3. B. A. Shawar and E. Atwell, A comparison between ALICE and Elizabeth chatbot systems. University of Leeds, School of Computing research report 2002.19, 2002.
  • 4. R. Wallace, “The elements of AIML style,” Alice AI Foundation, 2003.
  • 5. C. Stratton, “PyAIML: A Python AIML interpreter,” https://github.com/andelf/PyAIML.
  • 6. F. Bessho, T. Harada, and Y. Kuniyoshi, “Dialog system using real-time crowdsourcing and twitter large-scale corpus,” in Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp. 227-231, Association for Computational Linguistics, 2012.
  • 7. Twitter, Inc., “Twitter Streaming API,” https://dev.twitter.com/streaming/overview.
  • 8. R. Higashinaka, N. Kobayashi, T. Hirano, C. Miyazaki, T. Meguro, T. Makino, and Y. Matsuo, “Syntactic filtering and content-based retrieval of twitter sentences for the generation of system utterances in dialogue systems,” in Situated Dialog in Speech-Based Human-Computer Interaction, pp. 15-26, Springer, 2016.
  • 9. T. Kudo, “Mecab: Yet another part-of-speech and morphological analyzer,” http://mecab.sourceforge.net/, 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-428a39db-5101-4f4e-948c-7d18717e2739
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