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Author Jung, Sangkeun ♦ Lee, Cheongjae ♦ Kim, Kyungduk ♦ Lee, Gary Geunbae
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Dialog Simulation ♦ User Intention Modeling ♦ Lo-gistic Regression ♦ Data-driven Model ♦ Novel User Intention Si-mulation Method ♦ Data-driven Ap-proach ♦ Simulated User ♦ Gen-eration Time ♦ Self-directing Discourse Knowledge ♦ Diverse User Dis-course Knowledge ♦ Markov Logic Framework ♦ Various Type ♦ Hybrid Approach ♦ Discourse Knowledge ♦ Gener-ate User Intention Pattern ♦ Training Corpus ♦ Data-driven User Inten-tion Modeling ♦ Human Dialog Knowledge
Description This paper proposes a novel user intention si-mulation method which is a data-driven ap-proach but able to integrate diverse user dis-course knowledge together to simulate various type of users. In Markov logic framework, lo-gistic regression based data-driven user inten-tion modeling is introduced, and human dialog knowledge are designed into two layers such as domain and discourse knowledge, then it is integrated with the data-driven model in gen-eration time. Cooperative, corrective and self-directing discourse knowledge are designed and integrated to mimic such type of users. Experiments were carried out to investigate the patterns of simulated users, and it turned out that our approach was successful to gener-ate user intention patterns which are not only unseen in the training corpus and but also per-sonalized in the designed direction. 1
In Proc. of the Association for Computational Linguistics
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2009-01-01