Countries citing papers authored by Masayuki Asahara
Since
Specialization
Citations
This map shows the geographic impact of Masayuki Asahara'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 Masayuki Asahara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masayuki Asahara more than expected).
Fields of papers citing papers by Masayuki Asahara
This network shows the impact of papers produced by Masayuki Asahara. 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 Masayuki Asahara. The network helps show where Masayuki Asahara may publish in the future.
Co-authorship network of co-authors of Masayuki Asahara
This figure shows the co-authorship network connecting the top 25 collaborators of Masayuki Asahara.
A scholar is included among the top collaborators of Masayuki Asahara 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 Masayuki Asahara. Masayuki Asahara is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Oseki, Yohei & Masayuki Asahara. (2020). Design of BCCWJ-EEG : Balanced Corpus with Human Electroencephalography. Language Resources and Evaluation. 189–194.1 indexed citations
Asahara, Masayuki, et al.. (2020). Composing Word Vectors for Japanese Compound Words Using Bilingual Word Embeddings. Pacific Asia Conference on Language, Information, and Computation. 404–410.1 indexed citations
5.
Asahara, Masayuki, et al.. (2020). Generation and Evaluation of Concept Embeddings Via Fine-Tuning Using Automatically Tagged Corpus. Pacific Asia Conference on Language, Information, and Computation. 122–128.1 indexed citations
6.
Asahara, Masayuki, Hiroshi Kanayama, Takaaki Tanaka, et al.. (2018). Universal Dependencies Version 2 for Japanese.. Language Resources and Evaluation.10 indexed citations
7.
Asahara, Masayuki, et al.. (2018). All-words Word Sense Disambiguation Using Concept Embeddings. Language Resources and Evaluation.2 indexed citations
8.
Kato, Sachi, Masayuki Asahara, & Makoto Yamazaki. (2018). Annotation of 'Word List by Semantic Principles' Labels for the Balanced Corpus of Contemporary Written Japanese.. Waseda University Repository (Waseda University).2 indexed citations
9.
Asahara, Masayuki. (2017). Between Reading Time and Information Structure. Waseda University Repository (Waseda University). 15–24.3 indexed citations
10.
Asahara, Masayuki, et al.. (2016). Reading-Time Annotations for "Balanced Corpus of Contemporary Written Japanese".. International Conference on Computational Linguistics. 684–694.9 indexed citations
11.
Asahara, Masayuki, et al.. (2012). Identifying Temporal Relations by Sentence and Document Optimizations. International Conference on Computational Linguistics. 1371–1380.1 indexed citations
12.
Riedel, Sebastian, et al.. (2010). Coreference based event-argument relation extraction on biomedical text. UCL Discovery (University College London). 714. 90–98.1 indexed citations
13.
Asahara, Masayuki, et al.. (2010). A Structured Model for Joint Learning of Argument Roles and Predicate Senses. Meeting of the Association for Computational Linguistics. 98–102.18 indexed citations
14.
Asahara, Masayuki, et al.. (2008). Cocytus: parallel NLP over disparate data.. 49(4 Suppl). 271–293.1 indexed citations
15.
Cheng, Yuchang, Masayuki Asahara, & Yūji Matsumoto. (2008). Use of Event Types for Temporal Relation Identification in Chinese Text. International Joint Conference on Natural Language Processing. 31–38.3 indexed citations
16.
Jia, Lu, Masayuki Asahara, & Yūji Matsumoto. (2008). Analyzing Chinese Synthetic Words with Tree-based Information and a Survey on Chinese Morphologically Derived Words. International Joint Conference on Natural Language Processing. 53–60.2 indexed citations
17.
Asahara, Masayuki, et al.. (2006). Machine Learning-based Methods to Chinese Unknown Word Detection and POS Tag Guessing.. 16. 185–206.10 indexed citations
18.
Matsumoto, Yūji, et al.. (2006). An Annotated Corpus Management Tool: ChaKi.. Language Resources and Evaluation. 1418–1421.
19.
Asahara, Masayuki & Yuji Matsumoto. (2005). Training Multi-Classifiers for Chinese Unknown Word Detection.. 15(12). 1–12.2 indexed citations
20.
Asahara, Masayuki, et al.. (2004). Pruning False Unknown Words to Improve Chinese Word Segmentation. Pacific Asia Conference on Language, Information, and Computation. 139–150.3 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.