GOSSIP GALORE - A Conversational Web Agent for Collecting and Sharing Pop Trivia

Feiyu Xu, Peter Adolphs, Hans Uszkoreit, Xiwen Cheng, Hong Li

2009

Abstract

This paper presents a novel approach to a self-learning agent who collects and learns new knowledge from the web and exchanges her knowledge via dialogues with the users. The application domain is gossip about celebrities in the music world. The agent can inform herself and update the acquired knowledge by observing the web. Fans of musicians can ask for gossip information about stars, bands or people and groups related to them. This agent is built on top of information extraction, web mining, question answering and dialogue system technologies. The minimally supervised machine learning method for relation extraction gives the agent the capability to learn and update knowledge constantly from the web. The extracted relations are structured and linked with each other. Data mining is applied to the learned data to induce the social network among the artists and related people. The knowledge-intensive question answering technology enhanced by domain-specific inference and active memory allows the agent to have vivid and interactive conversations with users by utilizing natural language processing. Users can freely formulate their questions within the gossip data domain and access the answers in different ways: textual response, graph-based visualization of the related concepts and speech output.

References

  1. Burger, J., Cardie, C., Chaudhri, V., Gaizauskas, R., Harabagiu, S., Israel, D., Jacquemin, C., Lin, C.-Y., Maiorano, S., Miller, G., Moldovan, D., Ogden, B., Prager, J., Riloff, E., Singhal, A., Shrihari, R., Strzalkowski, T., Voorhees, E., and Weishedel, R. (2000). Issues, tasks and program structures to roadmap research in Question & Answering (Q&A).
  2. Drozdzynski, W., Krieger, H.-U., Piskorski, J., Schäfer, U., and Xu, F. (2004). Shallow processing with unification and typed feature structures - foundations and applications. Künstliche Intelligenz, 1:17-23.
  3. Jönsson, A., Andén, F., Degerstedt, L., Flycht-Eriksson, A., Merkel, M., and Norberg, S. (2004). Experiences from combining dialogue system development with information extraction techniques. In Maybury, M. T., editor, New Directions in Question Answering, pages 153-168. MIT Press.
  4. Klein, D. and Manning, C. D. (2003). Accurate unlexicalized parsing. In Proceedings of the 41st Meeting of the Association for Computational Linguistics (ACL 2003), pages 423-43.
  5. Krenn (2008). Responsive artificial situated cognitive agents living and learning on the internet. Poster presented at the International Conference on Cognitive Systems (CogSys 2008).
  6. Neumann, G. (2008). Strategien zur Webbasierten Multilingualen Fragebeantwortung: Wie Suchmaschinen zu Antwortmaschinen werden. Computer Science - Research and Development, 22(2):71-84.
  7. Reithinger, N., Herzog, G., and Blocher, A. (2007). SmartWeb - mobile broadband access to the semantic web. KI - Künstliche Intelligenz, 2/2007.
  8. Rosset, S., Galibert, O., Illouz, G., and Aurélien, M. (2006). Integrating spoken dialog and question answering: the Ritel project. In Proceedings of INTERSPEECH 2006.
  9. Schröder, M. and Hunecke, A. (2007). Mary tts participation in the Blizzard Challenge 2007. In Proceedings of the Blizzard Challenge 2007, Bonn, Germany.
  10. Strzalkowski, T., Small, S., Hardy, H., Yamrom, B., Liu, T., Kantor, P., Ng, K., and Wacholder, N. (2005). HITIQA: A question answering analytical tool. In Proceedings of the International Conference On Intelligence Analysis (IA-05), McLean, VA.
  11. Theune, M., Krahmer, E., van Schooten, B., op den Akker, R., van Hooijdonk, C., Marsi, E., Bosma, W., Hofs, D., and Nijholt, A. (2007). Questions, pictures, answers: Introducing pictures in question-answering systems. In Tenth international symposium on social communication, pages 450-463, Cuba.
  12. Xu, F., Uszkoreit, H., and Li, H. (2007). A seed-driven bottom-up machine learning framework for extracting relations of various complexity. Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 584-591.
  13. Xu, F., Uszkoreit, H., and Li, H. (2008a). Task driven coreference resolution for relation extraction. In Proceedings of the European Conference for Artificial Inteligence ECAI 2008, Patras, Greece.
  14. Xu, F., Uszkoreit, H., Li, H., and Felger, N. (2008b). Adaptation of relation extraction rules to new domains. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC 2008).
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Paper Citation


in Harvard Style

Xu F., Adolphs P., Uszkoreit H., Cheng X. and Li H. (2009). GOSSIP GALORE - A Conversational Web Agent for Collecting and Sharing Pop Trivia . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 115-122. DOI: 10.5220/0001663901150122


in Bibtex Style

@conference{icaart09,
author={Feiyu Xu and Peter Adolphs and Hans Uszkoreit and Xiwen Cheng and Hong Li},
title={GOSSIP GALORE - A Conversational Web Agent for Collecting and Sharing Pop Trivia},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={115-122},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001663901150122},
isbn={978-989-8111-66-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - GOSSIP GALORE - A Conversational Web Agent for Collecting and Sharing Pop Trivia
SN - 978-989-8111-66-1
AU - Xu F.
AU - Adolphs P.
AU - Uszkoreit H.
AU - Cheng X.
AU - Li H.
PY - 2009
SP - 115
EP - 122
DO - 10.5220/0001663901150122