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Bibrecord-Based Literature Management with Interactive Latent Space Learning

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From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries (ICADL 2022)

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Abstract

Every researcher must conduct a literature review, and the document management needs of researchers working on various research topics vary. However, there are two significant challenges today. First, traditional methods like the tree hierarchy of document folders and tag-based management are no longer effective with the enormous volume of publications. Second, although their bib information is available to everyone, many papers can be accessed only through paid services. This study attempts to develop an interactive tool for personal literature management solely based on their bibliographic records. To make such a tool possible, we developed a principled “human-in-the-loop latent space learning” method that estimates the management criteria of each researcher based on his or her feedback to calculate the positions of documents in a two-dimensional space on the screen. Since a set of bibliographic records forms a graph, our model is naturally designed as a graph-based encoder-decoder model that connects the graph and the space. The experiments with ten researchers from humanities, science, and engineering domains show that the proposed framework gives much superior results to a typical graph convolutional encoder-decoder model.

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Acknowledgement

This work was partially supported by Kumagai Gumi Co., Ltd., JSPS KAKENHI Grant Number 22H00508, 22K17944 and 21H03552. This work was approved by the IRB of University of Tsukuba. We are grateful to Masao Takaku for his valuable comments.

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Authors and Affiliations

  1. University of Tsukuba, Tsukuba, Japan

    Shingo Watanabe, Hiroyoshi Ito, Masaki Matsubara & Atsuyuki Morishima

Authors
  1. Shingo Watanabe
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  2. Hiroyoshi Ito
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  3. Masaki Matsubara
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  4. Atsuyuki Morishima
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Corresponding author

Correspondence to Shingo Watanabe .

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Editors and Affiliations

  1. National Taiwan Normal University, Taipei, Taiwan

    Yuen-Hsien Tseng

  2. Doshisha University, Kyoto, Japan

    Marie Katsurai

  3. VNU University of Engineering and Technology, Hanoi, Vietnam

    Hoa N. Nguyen

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Watanabe, S., Ito, H., Matsubara, M., Morishima, A. (2022). Bibrecord-Based Literature Management with Interactive Latent Space Learning. In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. Lecture Notes in Computer Science, vol 13636. Springer, Cham. https://doi.org/10.1007/978-3-031-21756-2_13

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  • DOI: https://doi.org/10.1007/978-3-031-21756-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21755-5

  • Online ISBN: 978-3-031-21756-2

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