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Similarity Retrieval Algorithm for Virtual Knowledge Graph

Research Project

Project/Area Number 22K18004
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 62020:Web informatics and service informatics-related
Research InstitutionJapan Advanced Institute of Science and Technology

Principal Investigator

RACHARAK Teeradaj  北陸先端科学技術大学院大学, 先端科学技術研究科, 講師 (30847512)

Project Period (FY) 2022-04-01 – 2025-03-31
Project Status Granted (Fiscal Year 2023)
Budget Amount *help
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2024: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2023: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2022: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
KeywordsVirtual Knowledge Graph / Similarity Algorithms / Information Retrieval / Explainable Similarity / Description Logic / Knowledge Graph / Analogical Reasoning
Outline of Research at the Start

Virtual knowledge graph (VKG) is an emerging research area that has received huge attention in recent years for integration and access of various databases. However, existing VKGs do not support the users to query similar information due to lack of similarity algorithms. Thus, we aim to develop novel algorithms based on Description Logics that can advance the querying of VKGs with explainable similarity, called "VKG-SIM". We envision that our proposed VKG-SIM will lay a solid ground for developing AI-based integration technologies that enable the utilization of diverse and massive data.

Outline of Annual Research Achievements

We have successfully implemented our prototype system called Virtual Knowledge Graph with Similar data (VKG-SIM). VKG-SIM is extended from the famous open source Ontop system and is implemented based on our algorithms for advancing the querying of VKG with an explainable similarity score. Thus, we could expect a high impact on the academic society and the industry. In addition, we have studied problems related to other KG systems.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

We have implemented our VKG-SIM system and conducted a preliminary analysis on its performance. Regarding our publication, we have published 1 journal paper (IEEE Access; Q1) and 5 international conference papers (ICAART, DSAI, KSE, ACIIDS, and ISWC).

Strategy for Future Research Activity

As for our next step, we completely develop our VKG-SIM system and evaluate based on real-world user scenarios in information retrieval. The goal of this year is to ensure practical correctness of the system and see how the proposed system can be applied beyond KG-based information retrieval.

Report

(2 results)
  • 2023 Research-status Report
  • 2022 Research-status Report
  • Research Products

    (7 results)

All 2024 2023 2022

All Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (6 results) (of which Int'l Joint Research: 6 results)

  • [Journal Article] WeExt: A Framework of Extending Deterministic Knowledge Graph Embedding Models for Embedding Weighted Knowledge Graphs2023

    • Author(s)
      Kun Kong Wei、Liu Xin、Racharak Teeradaj、Sun Guanqun、Chen Jianan、Ma Qiang、Nguyen Le-Minh
    • Journal Title

      IEEE Access

      Volume: 11 Pages: 48901-48911

    • DOI

      10.1109/access.2023.3276319

    • Related Report
      2023 Research-status Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Presentation] A Quantitative Assessment Framework for Modelling and Evaluation using Representation Learning in Smart Agriculture Ontology2024

    • Author(s)
      Khadija Meghraoui, Teeradaj Racharak, Kenza Ait El Kadi, Saloua Bensiali, Imane Sebari
    • Organizer
      n Proceedings of 16th International Conference on Agents and Artificial Intelligence (ICAART), Rome, Italy
    • Related Report
      2023 Research-status Report
    • Int'l Joint Research
  • [Presentation] BERT Fine-tuning the Covid-19 Open Research Dataset for Named Entity Recognition2023

    • Author(s)
      Shin Thant, Teeradaj Racharak, Frederic Andres
    • Organizer
      In Proceedings of the 1st International Conference of Data Science and Artificial Intelligence (DSAI), Bangkok, Thailand
    • Related Report
      2023 Research-status Report
    • Int'l Joint Research
  • [Presentation] Gender Bias Analysis in Commonsense Knowledge Graph Embeddings2023

    • Author(s)
      Khine Myat Thwe, Teeradaj Racharak, Minh Le Nguyen, Gender Bias Analysis in Commonsense Knowledge Graph Embeddings
    • Organizer
      In Proceedings of the 15th IEEE International Conference on Knowledge and Systems Engineering (KSE), Ha Noi, Vietnam
    • Related Report
      2023 Research-status Report
    • Int'l Joint Research
  • [Presentation] Can Ensemble Calibrated Learning enhance Link Prediction? A Study on Commonsense Knowledge2023

    • Author(s)
      Teeradaj Racharak, Watanee Jearanaiwongkul, Khine Myat Thwe
    • Organizer
      In LNAI Proceedings of 15th Asian Conference on Intelligent Information and Database Systems (ACIIDS), Phuket, Thailand
    • Related Report
      2023 Research-status Report
    • Int'l Joint Research
  • [Presentation] TransHExt: a Weighted Extension for TransH on Weighted Knowledge Graph Embedding2023

    • Author(s)
      Wei Kun Kong, Xin Liu, Teeradaj Racharak, Minh Le Nguyen
    • Organizer
      In Proceedings of the 21st International Semantic Web Conference (ISWC)
    • Related Report
      2023 Research-status Report
    • Int'l Joint Research
  • [Presentation] Doing Analogical Reasoning in Dynamic Assumption-based Argumentation Frameworks2022

    • Author(s)
      Teeradaj Racharak
    • Organizer
      The 34th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
    • Related Report
      2022 Research-status Report
    • Int'l Joint Research

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Published: 2022-04-19   Modified: 2024-12-25  

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