| 研究課題/領域番号 |
22K18004
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分62020:ウェブ情報学およびサービス情報学関連
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| 研究機関 | 北陸先端科学技術大学院大学 |
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研究代表者 |
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)
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2023年度)
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| 配分額 *注記 |
3,900千円 (直接経費: 3,000千円、間接経費: 900千円)
2024年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
2023年度: 1,690千円 (直接経費: 1,300千円、間接経費: 390千円)
2022年度: 1,040千円 (直接経費: 800千円、間接経費: 240千円)
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| キーワード | Virtual Knowledge Graph / Similarity Algorithms / Information Retrieval / Explainable Similarity / Description Logic / Knowledge Graph / Analogical Reasoning |
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| 研究開始時の研究の概要 |
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.
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| 研究実績の概要 |
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.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
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).
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| 今後の研究の推進方策 |
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.
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