Ting Liu
- Artificial Intelligence top 0.1%
- Information Systems top 0.2%
- Software top 1%
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Topics
- Topic Modeling (98 papers)Natural Language Processing Techniques (83 papers)Advanced Text Analysis Techniques (30 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Ting Liu
119 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 4.8k
- Information Systems 1.6k
- Software 518
- Computer Vision and Pattern Recognition 429
- Signal Processing 418
Countries citing papers authored by Ting Liu
This map shows the geographic impact of Ting Liu'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 Ting Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting Liu more than expected).
Fields of papers citing papers by Ting Liu
This network shows the impact of papers produced by Ting Liu. 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 Ting Liu. The network helps show where Ting Liu may publish in the future.
Co-authorship network of co-authors of Ting Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Ting Liu. A scholar is included among the top collaborators of Ting Liu 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 Ting Liu. Ting Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 10 | |
| 3 | 8 | |
| 4 | 3 | |
| 5 | 4 | |
| 6 | 4 | |
| 7 | 17 | |
| 8 | 45 | |
| 9 | Aspect Level Sentiment Classification with Deep Memory Networkbreakdown → | 675 |
| 10 | A Unified Architecture for Semantic Role Labeling and Relation Classification | 8 |
| 11 | Sentence Compression for Target-Polarity Word Collocation Extraction | 9 |
| 12 | Automatic Expansion of the MRC Psycholinguistic Database Imageability Ratings | 7 |
| 13 | 2 | |
| 14 | Building Chinese Event Type Paradigm Based on Trigger Clustering | 2 |
| 15 | A Weighted Voting Based Automatic Term Recognition Method | 1 |
| 16 | Bridging Topic Modeling and Personalized Search | 15 |
| 17 | 5 | |
| 18 | An Entity-Mention Model for Coreference Resolution with Inductive Logic Programming | 46 |
| 19 | Learning question paraphrases for QA from Encarta logs | 19 |
| 20 | Aligning Bilingual Corpora Using Sentences Location Information | 2 |
About Ting Liu
Ting Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 127 papers that have together received 5.8k indexed citations. Recurring topics across this work include Topic Modeling (98 papers), Natural Language Processing Techniques (83 papers) and Advanced Text Analysis Techniques (30 papers). The work is most often cited by research in Artificial Intelligence (4.8k citations), Software (518 citations) and Information Systems (1.6k citations). Ting Liu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Bing Qin, Duyu Tang, Ming Zhou, Xiaocheng Feng, Furu Wei, Nan Yang, Wanxiang Che, Zhangyin Feng, Nan Duan and Linjun Shou. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and Neurocomputing.
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.