Citations per year, relative to Nobuhiro Kaji Nobuhiro Kaji (= 1×)
peers
Takashi Inui
Countries citing papers authored by Nobuhiro Kaji
Since
Specialization
Citations
This map shows the geographic impact of Nobuhiro Kaji'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 Nobuhiro Kaji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nobuhiro Kaji more than expected).
This network shows the impact of papers produced by Nobuhiro Kaji. 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 Nobuhiro Kaji. The network helps show where Nobuhiro Kaji may publish in the future.
Co-authorship network of co-authors of Nobuhiro Kaji
This figure shows the co-authorship network connecting the top 25 collaborators of Nobuhiro Kaji.
A scholar is included among the top collaborators of Nobuhiro Kaji 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 Nobuhiro Kaji. Nobuhiro Kaji is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yoshinaga, Naoki, et al.. (2013). Modeling User Leniency and Product Popularity for Sentiment Classification. International Joint Conference on Natural Language Processing. 1107–1111.29 indexed citations
3.
Hasegawa, T., Nobuhiro Kaji, Naoki Yoshinaga, & Masashi Toyoda. (2013). Predicting and Eliciting Addressee's Emotion in Online Dialogue. Meeting of the Association for Computational Linguistics. 964–972.39 indexed citations
4.
Kaji, Nobuhiro & Masaru Kitsuregawa. (2013). Efficient Word Lattice Generation for Joint Word Segmentation and POS Tagging in Japanese. International Joint Conference on Natural Language Processing. 153–161.9 indexed citations
Kaji, Nobuhiro, et al.. (2012). A Study on Microblog Classification Based on Information Publicness.3 indexed citations
7.
Ren, Yong, Nobuhiro Kaji, Naoki Yoshinaga, Masashi Toyoda, & Masaru Kitsuregawa. (2011). Sentiment Classification in Resource-Scarce Languages by using Label Propagation. Pacific Asia Conference on Language, Information, and Computation. 420–429.5 indexed citations
8.
Kaji, Nobuhiro, et al.. (2011). Classification of users' attitudes toward rumors on microblogs. IEICE Technical Report; IEICE Tech. Rep.. 111(76). 55–60.2 indexed citations
9.
Kaji, Nobuhiro & Masaru Kitsuregawa. (2011). Splitting Noun Compounds via Monolingual and Bilingual Paraphrasing: A Study on Japanese Katakana Words. Empirical Methods in Natural Language Processing. 959–969.6 indexed citations
10.
Kaji, Nobuhiro, Yasuhiro Fujiwara, Naoki Yoshinaga, & Masaru Kitsuregawa. (2010). Efficient Staggered Decoding for Sequence Labeling. Meeting of the Association for Computational Linguistics. 485–494.12 indexed citations
Kaji, Nobuhiro & Masaru Kitsuregawa. (2007). Building Lexicon for Sentiment Analysis from Massive Collection of HTML Documents. Empirical Methods in Natural Language Processing. 1075–1083.154 indexed citations
14.
Kaji, Nobuhiro, et al.. (2004). Paraphrasing Predicates from Written Language to Spoken Language Using the Web.. North American Chapter of the Association for Computational Linguistics. 241–248.5 indexed citations
Kawahara, Daisuke, Nobuhiro Kaji, & Sadao Kurohashi. (2002). Question and Answering System based on Predicate-Argument Matching.. NTCIR.8 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.