A New Social Robot for Interactive Query-Based Summarization: Scientific Document Summarization

A New Social Robot for Interactive Query-Based Summarization: Scientific Document Summarization
International Conference On Interactive Collaborative Robotics ‪(ICR 2019)‬
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سه شنبه - ۲۹ مرداد ۱۳۹۸ تا يكشنبه - ۰۳ شهريور ۱۳۹۸
چکیده

The extractive summartization methods try to summarize a single or multiple documents based on informative sentences exactly as they appear in source(s).‎ One method to choose these sentences is to use users’ query, which could be problematic in many cases, specially in scientific context.‎ One way to tackle this challenge is to gather more information about the user and his preferences.‎ Therefore, in this paper we propose a novel framework to use the users’ feedbacks and a social robotics platform, Nao robot, has been adapted as an interacting agent.‎ This agent has multiple communication channels and could learn the user model and adapt to his/her needs via reinforcement learning approach.‎ The whole approach is then studied in terms of how much it is able to adapt based on user’s feedback, and also in terms of interaction time.‎

استناد: 

Zarinbal Masouleh, Marzieh, Azadeh Mohebi, Hesamoddin Mosalli, Razieh Haratinik, and Zahra Jabalameli.‎ 2019.‎ A New Social Robot for Interactive Query-Based Summarization: Scientific Document Summarization. Paper Presented in The 4TH International Conference On Interactive Collaborative Robotics (ICR 2019), Istanbul.‎

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