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International Conference on Robot Intelligence Technology and Applications

RiTA 2017: Robot Intelligence Technology and Applications 5 pp 49–61Cite as

Task-related Item-Name Discovery Using Text and Image Data from the Internet

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 751))

Abstract

There is a huge number of data on the Internet that can be used for the development of machine learning in a robot or an AI agent. Utilizing this unorganized data, however, usually requires pre-collected database, which is time-consuming and expensive to make. This paper proposes a framework for collecting names of items required for performing a task, using text and image data available on the Internet without relying on any dictionary or pre-made database. We demonstrate a method to use text data acquired from Google Search to estimate term frequency-inverse document frequency (TF-IDF) value for task-word-relation verification, then identify words that are likely to be an item-name using image classification. We show the comparison results of measuring words’ item-name likelihood using various image classification settings. Finally, we have demonstrated that our framework can discover more than 45% of the desired item-names on three example tasks.

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Author information

Authors and Affiliations

  1. Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Tokyo, Japan

    Putti Thaipumi & Osamu Hasegawa

Authors
  1. Putti Thaipumi
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  2. Osamu Hasegawa
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Corresponding author

Correspondence to Putti Thaipumi .

Editor information

Editors and Affiliations

  1. School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Jong-Hwan Kim

  2. Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Hyun Myung

  3. School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Junmo Kim

  4. Department of Mechanical Engineering, The University of Auckland, Auckland, New Zealand

    Weiliang Xu

  5. Department of Computer and Information Technology, Purdue University, West Lafayette, Indiana, USA

    Eric T Matson

  6. Department of Computer Science and Engineering, Dongguk University, Seoul, Korea (Republic of)

    Jin-Woo Jung

  7. Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Han-Lim Choi

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Cite this paper

Thaipumi, P., Hasegawa, O. (2019). Task-related Item-Name Discovery Using Text and Image Data from the Internet. In: Kim, JH., et al. Robot Intelligence Technology and Applications 5. RiTA 2017. Advances in Intelligent Systems and Computing, vol 751. Springer, Cham. https://doi.org/10.1007/978-3-319-78452-6_6

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