Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A Machine Learning Approach to Coreference Resolution of Noun Phrases
This map shows the geographic impact of Hwee Tou Ng'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 Hwee Tou Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hwee Tou Ng more than expected).
This network shows the impact of papers produced by Hwee Tou Ng. 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 Hwee Tou Ng. The network helps show where Hwee Tou Ng may publish in the future.
Co-authorship network of co-authors of Hwee Tou Ng
This figure shows the co-authorship network connecting the top 25 collaborators of Hwee Tou Ng.
A scholar is included among the top collaborators of Hwee Tou Ng 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 Hwee Tou Ng. Hwee Tou Ng is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chollampatt, Shamil & Hwee Tou Ng. (2018). A Reassessment of Reference-Based Grammatical Error Correction Metrics. International Conference on Computational Linguistics. 2730–2741.8 indexed citations
3.
He, Ruidan, Wee Sun Lee, Hwee Tou Ng, & Daniel Dahlmeier. (2018). Effective Attention Modeling for Aspect-Level Sentiment Classification. International Conference on Computational Linguistics. 1121–1131.94 indexed citations
4.
Chollampatt, Shamil, Kaveh Taghipour, & Hwee Tou Ng. (2016). Neural network translation models for grammatical error correction. International Joint Conference on Artificial Intelligence. 2768–2774.22 indexed citations
Wang, Pidong & Hwee Tou Ng. (2013). A Beam-Search Decoder for Normalization of Social Media Text with Application to Machine Translation. North American Chapter of the Association for Computational Linguistics. 471–481.29 indexed citations
Wu, Yuanbin & Hwee Tou Ng. (2013). Grammatical Error Correction Using Integer Linear Programming. Meeting of the Association for Computational Linguistics. 1456–1465.15 indexed citations
9.
Dahlmeier, Daniel, Hwee Tou Ng, & Siew Mei Wu. (2013). Building a Large Annotated Corpus of Learner English: The NUS Corpus of Learner English. 22–31.232 indexed citations
10.
Lin, Ziheng, Chang Liu, Hwee Tou Ng, & Min‐Yen Kan. (2012). Combining Coherence Models and Machine Translation Evaluation Metrics for Summarization Evaluation. National University of Singapore. 1. 1006–1014.15 indexed citations
11.
Ng, Hwee Tou, et al.. (2010). It Makes Sense: A Wide-Coverage Word Sense Disambiguation System for Free Text. National University of Singapore. 78–83.180 indexed citations
12.
Li, Junhui, Guodong Zhou, & Hwee Tou Ng. (2010). Joint Syntactic and Semantic Parsing of Chinese. National University of Singapore. 1108–1117.29 indexed citations
13.
Ng, Hwee Tou, et al.. (2009). Word sense disambiguation for all words without hard labor. National University of Singapore. 1616–1621.9 indexed citations
14.
Zhu, Conghui, et al.. (2007). A Unified Tagging Approach to Text Normalization. National University of Singapore. 688–695.13 indexed citations
15.
Li, Haizhou, et al.. (2007). A Statistical Language Modeling Approach to Lattice-Based Spoken Document Retrieval. Empirical Methods in Natural Language Processing. 9. 810–818.11 indexed citations
Ng, Hwee Tou, et al.. (2004). Chinese Part-of-Speech Tagging: One-at-a-Time or All-at-Once? Word-Based or Character-Based?. Empirical Methods in Natural Language Processing. 277–284.118 indexed citations
18.
Ng, Hwee Tou. (2004). One-at-a-Time or All-at-Once? Word-Based or Character-Based?. Empirical Methods in Natural Language Processing.1 indexed citations
19.
Ng, Hwee Tou, et al.. (2001). Question Answering Using a Large Text Database: A Machine Learning Approach. Empirical Methods in Natural Language Processing.14 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.