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Erschienen in:
Close-Loop Control of Microrobot Within a Constrained Environment Using Electromagnet Pairs Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

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

verfasst von : Marzieh Zarinbal, Azadeh Mohebi, Hesamoddin Mosalli, Razieh Haratinik, Zahra Jabalameli, Farnoush Bayatmakou

Erschienen in: Interactive Collaborative Robotics

Verlag: Springer International Publishing

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Abstract

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.

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Vorheriges Kapitel Emergency-Response Locomotion of Hexapod Robot with Heuristic Reinforcement Learning Using Q-Learning
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Metadaten
Titel
A New Social Robot for Interactive Query-Based Summarization: Scientific Document Summarization
verfasst von
Marzieh Zarinbal
Azadeh Mohebi
Hesamoddin Mosalli
Razieh Haratinik
Zahra Jabalameli
Farnoush Bayatmakou
Copyright-Jahr
2019
Buch
Interactive Collaborative Robotics

Print ISBN: 978-3-030-26117-7

Electronic ISBN: 978-3-030-26118-4

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-26118-4_32