Yao Meng
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Media Technology top 10%
- Molecular Biology
- Topics
- Natural Language Processing Techniques (19 papers)Topic Modeling (18 papers)Web Data Mining and Analysis (10 papers)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Yao Meng
48 papers receiving 330 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 220
- Computer Vision and Pattern Recognition 71
- Information Systems 59
- Media Technology 43
- Molecular Biology 18
Countries citing papers authored by Yao Meng
This map shows the geographic impact of Yao Meng'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 Yao Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yao Meng more than expected).
Fields of papers citing papers by Yao Meng
This network shows the impact of papers produced by Yao Meng. 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 Yao Meng. The network helps show where Yao Meng may publish in the future.
Co-authorship network of co-authors of Yao Meng
This figure shows the co-authorship network connecting the top 25 collaborators of Yao Meng. A scholar is included among the top collaborators of Yao Meng 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 Yao Meng. Yao Meng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 18 | |
| 5 | 9 | |
| 6 | A Distribution-based Model to Learn Bilingual Word Embeddings | 17 |
| 7 | DBpedia Entity Type Inference Using Categories. | 2 |
| 8 | Automatic Identifying Entity Type in Linked Data | 2 |
| 9 | 2 | |
| 10 | 7 | |
| 11 | 1 | |
| 12 | FRDC's Cross-lingual Entity Linking System at TAC 2013 | 5 |
| 13 | Semi-supervised Classification of Twitter Messages for Organization Name Disambiguation | 1 |
| 14 | An Adaptive Method for Organization Name Disambiguation with Feature Reinforcing | 3 |
| 15 | HPB SMT of FRDC Assisted by Paraphrasing for the NTCIR-9 PatentMT. | 2 |
| 16 | Extending the Hierarchical Phrase Based Model with Maximum Entropy Based BTG | 7 |
| 17 | Learning Phrase Boundaries for Hierarchical Phrase-based Translation | 3 |
| 18 | Morpheme-based product features categorization in Chinese reviews mining | 2 |
| 19 | Fault-Tolerant Learning for Term Extraction | 8 |
| 20 | 3 |
About Yao Meng
Yao Meng is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics, having authored 51 papers that have together received 355 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (19 papers), Topic Modeling (18 papers) and Web Data Mining and Analysis (10 papers). The work is most often cited by research in Artificial Intelligence (220 citations), Media Technology (43 citations) and Computer Vision and Pattern Recognition (71 citations). Yao Meng has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Hao Yu, Shuangyong Song, Zhongjun He, Wei Cui, Yingju Xia, Qingliang Miao, Ziwei Wang, Xin He, Jiejun Huang and Dongyou Zhang. Their work appears in journals such as Optics Express, Plant Cell & Environment and Sensors.
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.