Chunyu Kit

1.9k citations
73 papers · 1.0k indexed · h-index 17

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Text and Document Classification Technologies
    • Text Readability and Simplification
    • Sentiment Analysis and Opinion Mining
    • Speech Recognition and Synthesis

Papers in

    • Natural Language Processing Techniques 56
    • Topic Modeling 48
    • Advanced Text Analysis Techniques 11
    • Text Readability and Simplification 9
    • Algorithms and Data Compression 9
    • Sentiment Analysis and Opinion Mining 6

Chunyu Kit

70 papers receiving 963 citations

Peers

Chunyu Kit
Comparison fields: 5 of 86
  • Artificial Intelligence 879
  • Information Systems 142
  • Computer Vision and Pattern Recognition 115
  • Language and Linguistics 58
  • General Social Sciences 17
Replace Andréi Popescu-Belis with:
Andréi Popescu-Belis Switzerland
Stan Śzpakowicz Canada
Udo Kruschwitz United Kingdom
Diarmuid Ó Séaghdha United Kingdom
Enrique Alfonseca Spain
Loïc Barrault France
Omar F. Zaidan United States
José Camacho-Collados United Kingdom
Carina Silberer Germany
Rebecca Bruce United States
Chunyu Kit relative to Andréi Popescu-Belis Switzerland Andréi Popescu-Belis's profile →
Citations per field
00.5×3.4×
Andréi Popescu-Belis · 1×
Citations per year

Countries citing papers authored by Chunyu Kit

Since Specialization
Citations

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).

Fields of papers citing papers by Chunyu Kit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 25 scholars most cited alongside Chunyu Kit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chunyu Kit Line = papers co-authored together Chunyu Kit links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20235
2
Short and sparse text topic modeling via self-aggregation
2015103
3
Non-Monotonic Sentence Alignment via Semisupervised Learning
20134
4
Combine constituent and dependency parsing via reranking
20135
5
Finding More Bilingual Webpages with High Credibility via Link Analysis
20131
6
Higher-order Constituent Parsing and Parser Combination
20123
7
Entropy-based Training Data Selection for Domain Adaptation
201216
8
Extending Machine Translation Evaluation Metrics with Lexical Cohesion to Document Level
201241
9
Improving Part-of-speech Tagging for Context-free Parsing
20113
10
How Large a Corpus Do We Need: Statistical Method Versus Rule-based Method
20108
11
Incorporating Feature-based and Similarity-based Opinion Mining - CTL in NTCIR-8 MOAT
20103
12
Cross Lingual Opinion Analysis via Transfer Learning
20103
13
The Parameter-Optimized ATEC Metric for MT Evaluation
20105
14
Reranking with Multiple Features for Better Transliteration
20107
15
Comparative Evaluation of Online Machine Translation Systems with Legal Texts
200824
16
Exploiting Unlabeled Text with Different Unsupervised Segmentation Criteria for Chinese Word Segmentation
200818
17
An Improved Corpus Comparison Approach to Domain Specific Term Recognition
20081
18
An Empirical Comparison of Goodness Measures for Unsupervised Chinese Word Segmentation with a Unified Framework
200827
19
Integrating N-gram Model and Case-based Learning For Chinese Word Segmentation.
20042
20
Unsupervised Learning of Word Boundary with Description Length Gain
199946

About Chunyu Kit

Chunyu Kit is a scholar working on Artificial Intelligence, Language and Linguistics, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Information Systems, having authored 73 papers that have together received 1.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (56 papers), Topic Modeling (48 papers), Advanced Text Analysis Techniques (11 papers), Text Readability and Simplification (9 papers), Algorithms and Data Compression (9 papers), Handwritten Text Recognition Techniques (7 papers), Sentiment Analysis and Opinion Mining (6 papers) and Web Data Mining and Analysis (4 papers). The work is most often cited by research in Artificial Intelligence (879 citations), Information Systems (142 citations), Computer Vision and Pattern Recognition (115 citations), Language and Linguistics (58 citations) and General Social Sciences (17 citations). Chunyu Kit has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Jonathan J. Webster, Hai Zhao, Hai Zhao, Billy Tak Ming Wong, Xiaojun Quan, Yorick Wilks, Sinno Jialin Pan, Yong Ge, Guodong Zhou and Yan Song. Their work appears in journals such as Information Sciences, Humanities and Social Sciences Communications, Language Resources and Evaluation, Terminology International Journal of Theoretical and Applied Issues in Specialized Communication and Patterns.

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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