This map shows the geographic impact of Chunyu Kit'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 Chunyu Kit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chunyu Kit more than expected).
This network shows the impact of papers produced by Chunyu Kit. 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 Chunyu Kit. The network helps show where Chunyu Kit may publish in the future.
Co-authorship network of co-authors of Chunyu Kit
This figure shows the co-authorship network connecting the top 25 collaborators of Chunyu Kit.
A scholar is included among the top collaborators of Chunyu Kit 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 Chunyu Kit. Chunyu Kit is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Quan, Xiaojun, Chunyu Kit, Yong Ge, & Sinno Jialin Pan. (2015). Short and sparse text topic modeling via self-aggregation. CityU Scholars. 2270–2276.103 indexed citations
3.
Quan, Xiaojun, Chunyu Kit, & Yan Song. (2013). Non-Monotonic Sentence Alignment via Semisupervised Learning. Meeting of the Association for Computational Linguistics. 622–630.4 indexed citations
4.
Chen, Xiao Dong, et al.. (2013). Combine constituent and dependency parsing via reranking. International Joint Conference on Artificial Intelligence. 2155–2161.5 indexed citations
5.
Zhang, Chengzhi, Xuchen Yao, & Chunyu Kit. (2013). Finding More Bilingual Webpages with High Credibility via Link Analysis. CityU Scholars. 138–143.1 indexed citations
6.
Chen, Xiao Dong & Chunyu Kit. (2012). Higher-order Constituent Parsing and Parser Combination. Meeting of the Association for Computational Linguistics. 1–5.3 indexed citations
7.
Song, Yan, et al.. (2012). Entropy-based Training Data Selection for Domain Adaptation. International Conference on Computational Linguistics. 1191–1200.16 indexed citations
8.
Wong, Billy Tak Ming & Chunyu Kit. (2012). Extending Machine Translation Evaluation Metrics with Lexical Cohesion to Document Level. Empirical Methods in Natural Language Processing. 1060–1068.41 indexed citations
Zhao, Hai, Yan Song, & Chunyu Kit. (2010). How Large a Corpus Do We Need: Statistical Method Versus Rule-based Method. Language Resources and Evaluation.8 indexed citations
Wong, Billy Tak Ming & Chunyu Kit. (2010). The Parameter-Optimized ATEC Metric for MT Evaluation. Workshop on Statistical Machine Translation. 360–364.5 indexed citations
14.
Song, Yan, Chunyu Kit, & Hai Zhao. (2010). Reranking with Multiple Features for Better Transliteration. CityU Scholars. 62–65.7 indexed citations
15.
Kit, Chunyu, et al.. (2008). Comparative Evaluation of Online Machine Translation Systems with Legal Texts. Law library journal. 100(2). 299–321.24 indexed citations
16.
Zhao, Hai & Chunyu Kit. (2008). Exploiting Unlabeled Text with Different Unsupervised Segmentation Criteria for Chinese Word Segmentation. Research in computing science. 33. 93–104.18 indexed citations
17.
Liu, Xiaoyue & Chunyu Kit. (2008). An Improved Corpus Comparison Approach to Domain Specific Term Recognition. Waseda University Repository (Waseda University). 253–261.1 indexed citations
18.
Zhao, Hai & Chunyu Kit. (2008). An Empirical Comparison of Goodness Measures for Unsupervised Chinese Word Segmentation with a Unified Framework. CityU Scholars. 9–16.27 indexed citations
19.
Kit, Chunyu, Zhiming Xu, & Jonathan J. Webster. (2004). Integrating N-gram Model and Case-based Learning For Chinese Word Segmentation.. 14.2 indexed citations
20.
Kit, Chunyu & Yorick Wilks. (1999). Unsupervised Learning of Word Boundary with Description Length Gain. 1–6.46 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.