Ruihua Song
- Information Systems top 0.5%
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Co-authors
- Ji-Rong WenZhicheng DouTetsuya SakaiWei‐Ying MaHaifeng LiuShuyi ZhengJian‐Yun NieHsiao-Wuen Hon
- Topics
- Web Data Mining and Analysis (32 papers)Information Retrieval and Search Behavior (25 papers)Topic Modeling (21 papers)
- Journals
- IEEE Transactions on Knowledge and Data EngineeringInformation Processing & ManagementACM Transactions on Information Systems
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Ruihua Song
65 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Information Systems 1.3k
- Artificial Intelligence 804
- Signal Processing 286
- Computer Vision and Pattern Recognition 280
- Computer Networks and Communications 228
Countries citing papers authored by Ruihua Song
This map shows the geographic impact of Ruihua Song'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 Ruihua Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruihua Song more than expected).
Fields of papers citing papers by Ruihua Song
This network shows the impact of papers produced by Ruihua Song. 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 Ruihua Song. The network helps show where Ruihua Song may publish in the future.
Co-authorship network of co-authors of Ruihua Song
This figure shows the co-authorship network connecting the top 25 collaborators of Ruihua Song. A scholar is included among the top collaborators of Ruihua Song 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 Ruihua Song. Ruihua Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 9 | |
| 7 | Overview of the NTCIR-11 IMine Task | 33 |
| 8 | Overview of the NTCIR-10 INTENT-2 Task. | 32 |
| 9 | Overview of the NTCIR-9 INTENT Task | 46 |
| 10 | Microsoft Research Asia at the NTCIR-9 Intent Task. | 5 |
| 11 | Overview of NTCIR-8 ACLIA IR4QA. | 7 |
| 12 | 1 | |
| 13 | Microsoft Research Asia at the Web Track of TREC 2009 | 13 |
| 14 | Overview of the NTCIR-7 ACLIA Tasks: Advanced Cross-Lingual Information Access | 22 |
| 15 | NTCIR-7 ACLIA IR4QA Results based on Qrels Version 2. | 1 |
| 16 | Template-independent news extraction based on visual consistency | 40 |
| 17 | Microsoft Research Asia at Web Track and Terabyte Track of TREC 2004. | 40 |
| 18 | 5 | |
| 19 | THU TREC 2002: Novelty Track Experiments. | 4 |
| 20 | THU TREC2002 Web Track Experiments | 8 |
About Ruihua Song
Ruihua Song is a scholar working on Information Systems, Signal Processing and Computational Mathematics, having authored 69 papers that have together received 1.6k indexed citations. Recurring topics across this work include Web Data Mining and Analysis (32 papers), Information Retrieval and Search Behavior (25 papers) and Topic Modeling (21 papers). The work is most often cited by research in Information Systems (1.3k citations), Signal Processing (286 citations) and Artificial Intelligence (804 citations). Ruihua Song has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Ji-Rong Wen, Zhicheng Dou, Tetsuya Sakai, Wei‐Ying Ma, Haifeng Liu, Shuyi Zheng, Jian‐Yun Nie, Hsiao-Wuen Hon, Yong Yu and Xing Xie. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Information Processing & Management and ACM Transactions on Information Systems.
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.