Demo Data from SIGIR 2026 / reviewers in the wild / expert
Xiangqian Zhao
dblp:07/3503
· DBLP profile ↗
3ranked-venue papers
1as first author
2since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Face, body and person analysis · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Face, body and person analysis
person search |
1.0 | 1 | 2026 | A Multi-Granularity Scene-Aware Graph Convolution Method for Weakly Supervised Person Search · Int. J. Comput. Vis. 2026 |
Computer vision › Face, body and person analysis › person search
weakly supervised person search |
1.0 | 1 | 2026 | A Multi-Granularity Scene-Aware Graph Convolution Method for Weakly Supervised Person Search · Int. J. Comput. Vis. 2026 |
Bioinformatics and computational biology
molecular marker development |
0.1 | 1 | 2007 | PIP: a database of potential intron polymorphism markers · Bioinform. 2007 |
Bioinformatics and computational biology › genomics
plant genomics |
0.1 | 1 | 2007 | PIP: a database of potential intron polymorphism markers · Bioinform. 2007 |
Methods — techniques the papers use, named apart from their topics
graph convolution · 1.0sequence homology · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Hyperbolic geometry meets contrastive learning: A novel approach for complementary item recommendation
Xiangqian Zhao, Xiangxiang Liu, Zhijuan Du |
Expert Syst. Appl. | 1 |
| 2026 | A Multi-Granularity Scene-Aware Graph Convolution Method for Weakly Supervised Person Search
De Cheng, Haichun Tai, Nannan Wang 0001, Xiangqian Zhao, Jie Li 0001, Xinbo Gao 0001 |
Int. J. Comput. Vis. | 4 |
| 2007 | PIP: a database of potential intron polymorphism markersabstractMOTIVATION: With the recent progress made in large-scale plant functional genome sequencing projects, a great amount of EST (express sequence tag) data is becoming available. With the help of complete genomic sequence information of model plants (rice and Arabidopsis), it is possible to predict the joints between adjacent exons after splicing (or termed 'intron positions' for short) in homologous ESTs of other plants. This would allow developing potential intron polymorphism (PIP) markers in these plants by designing primers in exons flanking the target intron. RESULTS: We have extracted a total of 57,658 PIP markers in 59 plant species and created a web-based database platform named PIP to provide detailed information of these PIP markers and homologous relationships among PIP markers from different species. The platform also provides a function of online designing of PIP markers based on cDNA/EST sequences submitted by users. With evaluations performed in silico, we have found that the intron position prediction is highly reliable and the polymorphism level of PIP markers is high enough for practical need. AVAILABILITY: http://ibi.zju.edu.cn/pgl/pip/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Long Yang 0003, Gulei Jin, Xiangqian Zhao, Zhaohua Xu |
Bioinform. | 3 |