Legal information retrieval system relevant to R&D projects based on word-embedding of core terms

Hae Min Jung, Youna Lee, Wooju Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Generally, Research and development projects have relationship with statutes. Sometimes, new technologies developed in R&D projects can't be applied because they are restricted by newly enacted statutes. The situation comes from the fact that researchers don't know well about statutes that might affect their R&D projects. Therefore, we proposed a methodology to find relevant statutes with the R&D plan, based on cosine similarity of document vectors. R&D plan is a document which is written by researchers before they get into R&D, and it contains the main concepts about the project. In our method, a R&D plan is represented as a vector using network centrality. Then cosine similarity between the vector and TF-IDF vectors of statutes is calculated. After the calculation, statutes are provided with their ranks based on similarity values, so researchers can review and check them with priority. Compared to our previous study, this study differs in that we applied new variants of vectors to enhance the performance of our methodology and find a better representation for documents.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Electronic Commerce, ICEC 2017
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450353120
DOIs
Publication statusPublished - 2017 Aug 17
Event2017 International Conference on Electronic Commerce, ICEC 2017 - Pangyo, Seongnam, Korea, Republic of
Duration: 2017 Aug 172017 Aug 18

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2017 International Conference on Electronic Commerce, ICEC 2017
CountryKorea, Republic of
CityPangyo, Seongnam
Period17/8/1717/8/18

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Jung, H. M., Lee, Y., & Kim, W. (2017). Legal information retrieval system relevant to R&D projects based on word-embedding of core terms. In Proceedings of the International Conference on Electronic Commerce, ICEC 2017 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3154943.3154954