Knowledge Acquisition System Laboratory (Kato Laboratory) aims to develop a system that autonomously acquires knowledge from a large amount of statistical data on the Web, and a search engine that enables users to search for the acquired knowledge. Our laboratory mainly focuses on the following fields in Information Retrieval: retrieval models and ranking, learning to rank, search intent estimation, knowledge base development, knowledge base applications, Web mining, information extraction, search behavior analysis, search user models, recommendation systems, online evaluation.


WebSci 2023 Paper Accepted

Our paper “What Web Search Behaviors Lead to Online Purchase Satisfaction?”, authored by Yuki Yanagida, Makoto P. Kato, Yuka Kawada, Takehiro Yamamoto, Hiroaki Ohshima and Sumio Fujita, has been accepted at WebSci 2023 as a full paper.

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ECIR 2023 Paper Accepted

Our paper “Theoretical Analysis on the Efficiency of Interleaved Comparisons”, authored by Kojiro Iizuka, Hajime Morita and Makoto P. Kato, has been accepted at ECIR 2023 as a full paper.

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IPSJ TOD Journal Paper (Vol. 15, No. 1) Accepted

The following paper has been accepted at IPSJ TOD Journal (Vol. 15, No. 1):

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DBSJ Data Driven Studies (Vol. 1) Papers Accepted

The following paper has been accepted at DBSJ Data Driven Studies (Vol. 1): 中野 優, 加藤 誠: 被引用統計データのセル特定データセットの構築 柳田 雄輝,加藤 誠,河田 友香,山本 岳洋,大島 裕明,藤田 澄男: 検索行動に基づく購買満足度の関係分析

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ICADL 2022 Papers Accepted

Our papers “Can a Machine Reading Comprehension Model Improve Ad-hoc Document Retrieval?”, authored by Kota Usuha, Makoto P. Kato, and Sumio Fujita, and “Active Learning for Efficient Partial Improvement of Learning to Rank”, authored by Koki Shibata and Makoto P. Kato, have been accepted at ICADL 2022 as short papers.

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Data Science and Engineering Paper Accepted

The following paper has been accepted at Data Science and Engineering: Atsuki Maruta, Makoto P. Kato: Intent-Aware Data Visualization Recommendation

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Ando-san (M2) and Shinden-san (M1)’s Proposal Got Accepted by 2022 Tsukuba-city’s Project for Supporting Society 5.0 Implementation Trials

A proposal by 合同会社大人検索, which is a company led by Ando-san (M2) and Shinden-san (M1), “Demonstration Experiment of Oudan Sharing ー A System for Enabling Smooth Information Sharing in Organizations by Graph Databases” (グラフデータベースを活用した組織内での情報共有を円滑にするシステム「Oudan Sharing」の実証実験) got accepted by 2022 Tsukuba-city’s project for supporting Society 5.0 implementation trials (令和4年度つくばSociety 5.0社会実装トライアル支援事業). Proposal Overview (in Japanese) (PDF 2.9MB) […]

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Usuha-san (M1) received the Poster Presentation Award at the NTCIR-16 Conference

Usuha-san (M1) received the Poster Presentation Award at the NTCIR-16 Conference! 👏👏👏  Kota Usuha, Kohei Shinden, Makoto P. Kato and Sumio Fujita. KASYS at the NTCIR-16 WWW-4 Task. The 16th NTCIR Conference

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Research Topics

Visualizing Data

Search by Analogy