Hideki Isozaki

2.2k total citations
70 papers, 1.5k citations indexed

About

Hideki Isozaki is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Hideki Isozaki has authored 70 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Information Systems. Recurrent topics in Hideki Isozaki's work include Topic Modeling (51 papers), Natural Language Processing Techniques (50 papers) and Speech and dialogue systems (12 papers). Hideki Isozaki is often cited by papers focused on Topic Modeling (51 papers), Natural Language Processing Techniques (50 papers) and Speech and dialogue systems (12 papers). Hideki Isozaki collaborates with scholars based in Japan and United States. Hideki Isozaki's co-authors include Jun Suzuki, Hajime Tsukada, Hideto Kazawa, Tsutomu Hirao, Katsuhito Sudoh, Kevin Duh, Taro Watanabe, Ryuichiro Higashinaka, Eisaku Maeda and Akinori Fujino and has published in prestigious journals such as Future Generation Computer Systems, Information Processing & Management and Information Processing Letters.

In The Last Decade

Hideki Isozaki

67 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hideki Isozaki Japan 20 1.4k 190 160 89 38 70 1.5k
Masaaki Nagata Japan 22 1.7k 1.2× 273 1.4× 135 0.8× 59 0.7× 18 0.5× 161 1.8k
Guohong Fu China 15 905 0.6× 112 0.6× 96 0.6× 140 1.6× 61 1.6× 62 969
Jingbo Zhu China 17 1.0k 0.7× 203 1.1× 104 0.7× 42 0.5× 22 0.6× 104 1.1k
Tushar Khot United States 18 1.2k 0.9× 342 1.8× 181 1.1× 63 0.7× 56 1.5× 48 1.4k
Vasin Punyakanok United States 10 858 0.6× 56 0.3× 93 0.6× 85 1.0× 24 0.6× 20 902
Peter J. Liu United States 4 2.0k 1.4× 366 1.9× 268 1.7× 82 0.9× 45 1.2× 4 2.1k
Duncan A. J. Blythe Germany 9 642 0.5× 62 0.3× 86 0.5× 95 1.1× 65 1.7× 14 852
Eric K. Ringger United States 18 712 0.5× 131 0.7× 59 0.4× 31 0.3× 12 0.3× 61 829
Claire Bonial United States 13 1.0k 0.7× 126 0.7× 74 0.5× 98 1.1× 18 0.5× 47 1.1k
Stefan Riezler Germany 21 1.6k 1.1× 208 1.1× 238 1.5× 85 1.0× 36 0.9× 74 1.7k

Countries citing papers authored by Hideki Isozaki

Since Specialization
Citations

This map shows the geographic impact of Hideki Isozaki's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hideki Isozaki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideki Isozaki more than expected).

Fields of papers citing papers by Hideki Isozaki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hideki Isozaki. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hideki Isozaki. The network helps show where Hideki Isozaki may publish in the future.

Co-authorship network of co-authors of Hideki Isozaki

This figure shows the co-authorship network connecting the top 25 collaborators of Hideki Isozaki. A scholar is included among the top collaborators of Hideki Isozaki based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hideki Isozaki. Hideki Isozaki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Isozaki, Hideki, et al.. (2015). Detection of Mathematical Formula Regions in Images of Scientific Papers by using Deep Learning and OCR. IEICE Technical Report; IEICE Tech. Rep.. 115(347). 19–24. 1 indexed citations
2.
Isozaki, Hideki, Tsutomu Hirao, Kevin Duh, Katsuhito Sudoh, & Hajime Tsukada. (2010). Automatic Evaluation of Translation Quality for Distant Language Pairs. Empirical Methods in Natural Language Processing. 944–952. 190 indexed citations
3.
Isozaki, Hideki, Katsuhito Sudoh, Hajime Tsukada, & Kevin Duh. (2010). Head Finalization: A Simple Reordering Rule for SOV Languages. Workshop on Statistical Machine Translation. 244–251. 59 indexed citations
4.
Duh, Kevin, Katsuhito Sudoh, Hajime Tsukada, Hideki Isozaki, & Masaaki Nagata. (2010). N-Best Reranking by Multitask Learning. Workshop on Statistical Machine Translation. 375–383. 11 indexed citations
5.
Hayashi, Katsuhiko, Taro Watanabe, Hajime Tsukada, & Hideki Isozaki. (2009). Structural Support Vector Machines for Log-Linear Approach in Statistical Machine Translation. IWSLT. 144–151. 4 indexed citations
6.
Suzuki, Jun & Hideki Isozaki. (2008). Semi-Supervised Sequential Labeling and Segmentation Using Giga-Word Scale Unlabeled Data. Meeting of the Association for Computational Linguistics. 665–673. 86 indexed citations
7.
Higashinaka, Ryuichiro & Hideki Isozaki. (2008). Corpus-based Question Answering for why-Questions. International Joint Conference on Natural Language Processing. 418–425. 48 indexed citations
8.
Fujino, Akinori, Hideki Isozaki, & Jun Suzuki. (2008). Multi-label Text Categorization with Model Combination based on F1-score Maximization.. International Joint Conference on Natural Language Processing. 823–828. 31 indexed citations
9.
Fujino, Akinori & Hideki Isozaki. (2008). Multi-label Classification using Logistic Regression Models for NTCIR-7 Patent Mining Task. NTCIR. 4 indexed citations
10.
Higashinaka, Ryuichiro & Hideki Isozaki. (2007). NTT's Question Answering System for NTCIR-6 QAC-4. NTCIR. 4 indexed citations
11.
Watanabe, Taro, Jun Suzuki, Katsuhito Sudoh, Hajime Tsukada, & Hideki Isozaki. (2007). Larger Feature Set Approach for Machine Translation in IWSLT 2007. IWSLT. 111–118. 1 indexed citations
12.
Suzuki, Jun, Akinori Fujino, & Hideki Isozaki. (2007). Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach. Empirical Methods in Natural Language Processing. 791–800. 23 indexed citations
13.
Watanabe, Taro, Jun Suzuki, Hajime Tsukada, & Hideki Isozaki. (2007). Online Large-Margin Training for Statistical Machine Translation. Empirical Methods in Natural Language Processing. 764–773. 127 indexed citations
14.
Fujino, Akinori & Hideki Isozaki. (2007). Multi-label Patent Classification at NTT Communication Science Laboratories. NTCIR. 3 indexed citations
15.
Watanabe, Taro, Jun Suzuki, Hajime Tsukada, & Hideki Isozaki. (2006). NTT statistical machine translation for IWSLT 2006.. IWSLT. 95–102. 12 indexed citations
16.
Tsukada, Hajime, Taro Watanabe, Jun Suzuki, Hideto Kazawa, & Hideki Isozaki. (2005). The NTT Statistical Machine Translation System for IWSLT2005. IWSLT. 112–117. 4 indexed citations
17.
Isozaki, Hideki, Katsuhito Sudoh, & Hajime Tsukada. (2005). NTT's Japanese-English Cross-Language Question Answering System. NTCIR. 5 indexed citations
18.
Kazawa, Hideto, Tsutomu Hirao, Hideki Isozaki, & Eisaku Maeda. (2002). A Machine Learning Approach for QA and Novelty Tracks: NTT System Description.. Text REtrieval Conference. 9 indexed citations
19.
Sasaki, Yutaka, et al.. (2002). NTT's QA Systems for NTCIR QAC-1.. NTCIR. 15 indexed citations
20.
Isozaki, Hideki & Yoav Shoham. (1992). A Mechanism for Reasoning about Time and Belief.. Future Generation Computer Systems. 694–701. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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