• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2016 Fiscal Year Annual Research Report

文脈を考慮した数学的知識へのアクセスに関する研究

Research Project

Project/Area Number 14J09896
Research InstitutionThe University of Tokyo

Principal Investigator

KRISTIANTO GIOVANNIYOKO  東京大学, 情報理工学系研究科, 特別研究員(DC1)

Project Period (FY) 2014-04-25 – 2017-03-31
KeywordsMathematical knowledge / Math formulae search / Mathematical expressions / MathML indexing / Dependency graph / Math entity linking
Outline of Annual Research Achievements

The objective of this research is to design a mathematical information access (MIA) system, that is a system that allows people to effectively access and process large amounts of mathematical information. We propose a math information retrieval (MIR) module to allow effective search for math information. Then, we design a math entity linking (MEL) module for document browsing. This latter module provides information about math expressions contained in each document by linking these math expressions to their corresponding articles in Wikipedia.

In this year, what we have achieved are:
(1) The evaluation of our MIR module in the NTCIR-12 MathIR task. The results showed that our system finished at the first place. The overall results were published in the 12th NTCIR conference. In addition, the detail of the key component of our MIR module was published in the Information Retrieval Journal.
(2) The initial design of MEL module. Our initial MEL module was based on the MIR. The evaluation showed that the initial module did not perform well. This result was published in the 18th ICADL.
(3) The development of a supervised-learning approach for MEL. We constructed a dataset for this task, then proposed a method for measuring the importance of a given math expressions in its containing document, and finally implemented several features (i.e. math and text similarity, math importance, and math prominence). It was shown that the latter MEL module achieved a precision of 83.40%, compared with 6.22% for our initial module. This work was published in the SWM at WSDM 2017 conference.

Research Progress Status

28年度が最終年度であるため、記入しない。

Strategy for Future Research Activity

28年度が最終年度であるため、記入しない。

  • Research Products

    (4 results)

All 2017 2016

All Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results,  Acknowledgement Compliant: 1 results) Presentation (3 results) (of which Int'l Joint Research: 3 results)

  • [Journal Article] Utilizing Dependency Relationships between Math Expressions in Math IR2017

    • Author(s)
      Giovanni Yoko Kristianto, Goran Topic, Akiko Aizawa
    • Journal Title

      Information Retrieval Journal

      Volume: 20 Pages: 132--167

    • DOI

      10.1007/s10791-017-9296-8

    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Presentation] Linking Mathematical Expressions to Wikipedia2017

    • Author(s)
      Giovanni Yoko Kristianto, Akiko Aizawa
    • Organizer
      Workshop on Scholarly web Mining (SWM) at WSDM 2017
    • Place of Presentation
      The Guildhall (Cambridge, United Kingdom)
    • Year and Date
      2017-02-10 – 2017-02-10
    • Int'l Joint Research
  • [Presentation] Entity Linking for Mathematical Expressions in Scientific Documents2016

    • Author(s)
      Giovanni Yoko Kristianto, Goran Topic, Akiko Aizawa
    • Organizer
      The 18th International Conference on Asia-Pacific Digital Libraries (ICADL)
    • Place of Presentation
      University of Tsukuba (Tsukuba, Ibaraki, Japan)
    • Year and Date
      2016-12-05 – 2016-12-09
    • Int'l Joint Research
  • [Presentation] MCAT Math Retrieval System for NTCIR-12 MathIR Task2016

    • Author(s)
      Giovanni Yoko Kristianto, Goran Topic, Akiko Aizawa
    • Organizer
      The 12th NTCIR Conference
    • Place of Presentation
      National Institute of Informatics (Chiyoda-ku, Tokyo, Japan)
    • Year and Date
      2016-06-07 – 2016-06-10
    • Int'l Joint Research

URL: 

Published: 2018-01-16  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi