📰 SIGHAN Workshop on Chinese Language Processing 2003 — accepted papers

SIGHAN Workshop on Chinese Language Processing 2003 is the 2003 edition of the SIGHAN Workshop on Chinese Language Processing, held in Sapporo, Japan, July 2003 (publisher: Association for Computational Linguistics). OpenAlex lists 31 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

All accepted papers (31)

The most cited first; 2 with our summary link to their page here, the others to the original.

1. A Bottom-up Merging Algorithm for Chinese Unknown Word ExtractionWei-Yun Ma, Keh-Jiann Chen
2. A Chinese Efficient Analyser Integrating Word Segmentation, Part-Of-Speech Tagging, Partial Parsing and Full ParsingGuoDong Zhou, Jian Su
3. A Two-stage Statistical Word Segmentation System for ChineseGuohong Fu, Kang-Kwong Luke
4. A Unicode Based Adaptive SegmentorQ. Lu, S. T. Chan, R. F. Xu et al.
5. Abductive Explanation-based Learning Improves Parsing Accuracy and EfficiencyOliver Streiter
6. Annotating the Propositions in the Penn Chinese TreebankNianwen Xue, Martha Palmer
7. Building a Large Chinese Corpus Annotated with Semantic DependencyMingqin Li, Juanzi Li, Zhendong Dong et al.
8. CHINERS: A Chinese Named Entity Recognition System for the Sports DomainTianfang Yao, Wei Ding, Gregor Erbach
9. Chinese Lexical Analysis Using Hierarchical Hidden Markov ModelHua-Ping Zhang, Qun Liu, Xue-Qi Cheng et al.
10. Chinese Word Segmentation Using Minimal Linguistic KnowledgeAitao Chen
11. Chinese Word Segmentation as LMR TaggingNianwen Xue, Libin Shen
12. Chinese Word Segmentation at Peking UniversityHuiming Duan, Xiaojing Bai, Baobao Chang et al.
13. Chinese Word Segmentation in MSR-NLPAndi Wu
14. Chunking-based Chinese Word TokenizationGuoDong Zhou
15. Class Based Sense Definition Model for Word Sense Tagging and DisambiguationTracy Lin, Jason S. Chang
16. Combining Segmenter and Chunker for Chinese Word SegmentationMasayuki Asahara, Chooi Ling Goh, Xiaojie Wang et al.
17. HHMM-based Chinese Lexical Analyzer ICTCLASHua-Ping Zhang, Hong-Kui Yu, De-Yi Xiong et al.our summary
18. Integrating Ngram Model and Case-based Learning for Chinese Word SegmentationChunyu Kit, Zhiming Xu, Jonathan J. Webster
19. Introduction to CKIP Chinese Word Segmentation System for the First International Chinese Word Segmentation BakeoffWei-Yun Ma, Keh-Jiann Chen
20. Learning Verb-Noun Relations to Improve ParsingAndi Wu
21. Modeling of Long Distance Context Dependency in ChineseGuoDong Zhou
22. News-Oriented Automatic Chinese Keyword IndexingSujian Li, Houfeng Wang, Shiwen Yu et al.
23. SYSTRAN's Chinese Word SegmentationJin Yang, Jean Senellart, Remi Zajac
24. Semantic Maps for Word Alignment in Bilingual Parallel CorporaQing Ma, Yujie Zhang, Masaki Murata et al.
25. Single Character Chinese Named Entity RecognitionXiaodan Zhu, Mu Li, Jianfeng Gao et al.

See all 31 papers in SIGHAN Workshop on Chinese Language Processing 2003 — accepted papers →

📄 Papers with our summary in our library (2)

The most cited first (OpenAlex citations plus our library's).

1. HHMM-based Chinese Lexical Analyzer ICTCLASSIGHAN Workshop on Chinese Language ProcessingHua-Ping Zhang, Hong-Kui Yu, De-Yi Xiong, et al.2003 · 527 citations
2. The First International Chinese Word Segmentation BakeoffSIGHAN Workshop on Chinese Language ProcessingRichard Sproat, Thomas Emerson2003 · 286 citations

🧭 Top topics

Topics of its works in our library, with the number of works on each.

🔤Part-of-speech tagging (1)✂️Tokenization & segmentation (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (2)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🏢AT&TBedminster · United States1 work here🏛️Chinese Academy of SciencesBeijing · China1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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