Niyu Ge

542 total citations
17 papers, 336 citations indexed

About

Niyu Ge is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Niyu Ge has authored 17 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 5 papers in Information Systems and 4 papers in Computer Networks and Communications. Recurrent topics in Niyu Ge's work include Topic Modeling (9 papers), Natural Language Processing Techniques (9 papers) and Software System Performance and Reliability (4 papers). Niyu Ge is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (9 papers) and Software System Performance and Reliability (4 papers). Niyu Ge collaborates with scholars based in United States. Niyu Ge's co-authors include Eugene Charniak, John Hale, Xiaolan Zhang, Vasanth Bala, Jiaqi Zhang, Yuanyuan Zhou, Tianyin Xu, Kai Fan, Boxing Chen and Pei Zhang and has published in prestigious journals such as ACM SIGPLAN Notices, Language Resources and Evaluation and Meeting of the Association for Computational Linguistics.

In The Last Decade

Niyu Ge

17 papers receiving 292 citations

Peers

Niyu Ge

AI

IS

CNC

MB

SOFTW

Martin Homola Slovakia

Hans-Jürgen Profitlich Germany

Tommaso Soru Germany

Philipp Heim Germany

Inma Hernández Spain

Benoit Lavoie United States

Frithjof Dau Australia

Deming Ye China

Lewis Hart Canada

Martin Homola Slovakia

Niyu Ge

139 ×0.6

AI

54 ×0.5

IS

54 ×0.5

CNC

25 ×1.1

MB

6 ×0.3

SOFTW

Citations per year, relative to Niyu Ge Niyu Ge (= 1×) peers Martin Homola

Countries citing papers authored by Niyu Ge

Since Specialization

Citations

This map shows the geographic impact of Niyu Ge'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 Niyu Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niyu Ge more than expected).

Fields of papers citing papers by Niyu Ge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Niyu Ge. 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 Niyu Ge. The network helps show where Niyu Ge may publish in the future.

Co-authorship network of co-authors of Niyu Ge

This figure shows the co-authorship network connecting the top 25 collaborators of Niyu Ge. A scholar is included among the top collaborators of Niyu Ge 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 Niyu Ge. Niyu Ge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

1.

Zhang, Pei, Boxing Chen, Niyu Ge, & Kai Fan. (2020). Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation. 1081–1087. 21 indexed citations

2.

Fan, Kai, Bo Li, Jiayi Wang, et al.. (2020). Neural Zero-Inflated Quality Estimation Model for Automatic Speech Recognition System. 606–610. 3 indexed citations

3.

Wang, Ke, et al.. (2020). Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing. 2175–2186. 3 indexed citations

4.

Zhang, Jiaqi, Xiaolan Zhang, Niyu Ge, et al.. (2014). EnCore. ACM SIGARCH Computer Architecture News. 42(1). 687–700. 6 indexed citations

5.

Zhang, Jiaqi, Xiaolan Zhang, Niyu Ge, et al.. (2014). EnCore. 687–700. 71 indexed citations

6.

Ge, Niyu, et al.. (2014). Understanding the role of sentiment analysis in contract risk classification. 1–6. 3 indexed citations

7.

Zhang, Jiaqi, Xiaolan Zhang, Niyu Ge, et al.. (2014). EnCore. ACM SIGPLAN Notices. 49(4). 687–700. 8 indexed citations

8.

Bai, Kun, et al.. (2013). What to discover before migrating to the cloud. Integrated Network Management. 320–327. 18 indexed citations

9.

Ni, Jian, et al.. (2013). A statistical machine learning approach for ticket mining in IT service delivery. Integrated Network Management. 541–546. 10 indexed citations

10.

Xiang, Bing, Niyu Ge, & Abraham Ittycheriah. (2011). Improving Reordering for Statistical Machine Translation with Smoothed Priors and Syntactic Features. Meeting of the Association for Computational Linguistics. 61–69. 8 indexed citations

11.

Ge, Niyu, et al.. (2010). Enriching Word Alignment with Linguistic Tags. Language Resources and Evaluation. 14 indexed citations

12.

Strassel, Stephanie, Xiaoyi Ma, Niyu Ge, et al.. (2010). Parallel Aligned Treebank Corpora at LDC: Methodology, Annotation and Integration. DSpace repository (University of Tartu). 3 indexed citations

13.

Ge, Niyu. (2010). A Direct Syntax-Driven Reordering Model for Phrase-Based Machine Translation. 849–857. 12 indexed citations

14.

Ge, Niyu, Abe Ittycheriah, & Kishore Papineni. (2008). Multiple reorderings in phrase-based machine translation. 61–68. 2 indexed citations

15.

Zhao, Bing, Niyu Ge, & Kishore Papineni. (2005). Inner-outer bracket models for word alignment using hidden blocks. 177–184. 4 indexed citations

16.

Charniak, Eugene & Niyu Ge. (2000). An approach to anaphoric pronouns. 2 indexed citations

17.

Ge, Niyu, John Hale, & Eugene Charniak. (1998). A Statistical Approach to Anaphora Resolution. Meeting of the Association for Computational Linguistics. 148 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.

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