• 1111 引用
  • 18 h指数
19982019
Pureに変更を加えた場合、すぐここに表示されます。

Fingerprint Tetsuya Sakaiが取り組む研究トピックをご確認ください。これらのトピックラベルは、この人物の研究に基づいています。これらを共に使用することで、固有の認識が可能になります。

  • 1 同様のプロファイル
Information retrieval Engineering & Materials Science
Experiments Engineering & Materials Science
Search engines Engineering & Materials Science
Websites Engineering & Materials Science
Feedback Engineering & Materials Science
Statistical tests Engineering & Materials Science
Metric Mathematics
Information retrieval systems Engineering & Materials Science

ネットワーク 最近の共同研究。丸をクリックして詳細を確認しましょう。

研究成果 1998 2019

A Comparative Study of Deep Learning Approaches for Query-Focused Extractive Multi-Document Summarization

Yuliska & Sakai, T., 2019 5 9, 2019 IEEE 2nd International Conference on Information and Computer Technologies, ICICT 2019. Institute of Electrical and Electronics Engineers Inc., p. 153-157 5 p. 8710851. (2019 IEEE 2nd International Conference on Information and Computer Technologies, ICICT 2019).

研究成果: Conference contribution

learning
neural network
Experiments
performance
Summarization

Attitude detection for one-round conversation: Jointly extracting target-polarity pairs

Zeng, Z., Lin, P., Song, R. & Sakai, T., 2019 1 30, WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, p. 285-293 9 p. (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining).

研究成果: Conference contribution

BM25 Pseudo Relevance Feedback using Anserini at Waseda university

Zeng, Z. & Sakai, T., 2019 1 1, : : CEUR Workshop Proceedings. 2409, p. 62-63 2 p.

研究成果: Conference article

Tuning
Feedback

Centre@clef2019: Overview of the replicability and reproducibility tasks

Ferro, N., Fuhr, N., Maistro, M., Sakai, T. & Soboroff, I., 2019 1 1, : : CEUR Workshop Proceedings. 2380

研究成果: Conference article

2 引用 (Scopus)

Centre@clef 2019

Ferro, N., Fuhr, N., Maistro, M., Sakai, T. & Soboroff, I., 2019 1 1, Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Stein, B., Mayr, P., Azzopardi, L., Fuhr, N., Hauff, C. & Hiemstra, D. (版). Springer-Verlag, p. 283-290 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 11438 LNCS).

研究成果: Conference contribution

Reproducibility
Information retrieval
Additivity
Incentives
Information Retrieval