Demo Data from VLDB 2026 / reviewers in the wild / expert
Zuoxi Yang
dblp:231/8543
· DBLP profile ↗
4ranked-venue papers
4as first author
2since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-author · 1 since 2021Databases, data management, data science and information retrieval · 2 · 2 first-author · 1 since 2021
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.
| Databases, data mining, and information retrieval
2 papers |
Knowledge graphs · 39% Information retrieval · 39% Recommender systems · 22% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Recommender systems › explainable recommendation
explanation generation |
0.6 | 1 | 2022 | Generating Knowledge-based Explanation for Recommendation from Review · SIGIR 2022 |
Information retrieval › document retrieval › domain-specific retrieval
biomedical information retrieval |
0.4 | 1 | 2020 | Biomedical Information Retrieval incorporating Knowledge Graph for Explainable Precision Medicine · SIGIR 2020 |
Information retrieval › document retrieval › domain-specific retrieval › biomedical information retrieval
precision medicine search |
0.4 | 1 | 2020 | Biomedical Information Retrieval incorporating Knowledge Graph for Explainable Precision Medicine · SIGIR 2020 |
Information retrieval › multimedia analysis and retrieval
semantic gap |
0.1 | 1 | 2020 | Biomedical Information Retrieval incorporating Knowledge Graph for Explainable Precision Medicine · SIGIR 2020 |
Methods — techniques the papers use, named apart from their topics
review mining · 0.6knowledge graph embedding · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Generating Knowledge-based Explanation for Recommendation from ReviewabstractReasonable explanation is helpful to increase the trust and satisfaction of user to the recommender system. Among many previous studies, there is growing concern about generating explanation based on review text. Zuoxi Yang |
SIGIR | 1 |
| 2021 | GFE: General Knowledge Enhanced Framework for Explainable Sequential Recommendation
Zuoxi Yang, Shoubin Dong, Jinlong Hu 0002 |
Knowl. Based Syst. | 1 |
| 2020 | Biomedical Information Retrieval incorporating Knowledge Graph for Explainable Precision MedicineabstractAs for many complex diseases, there is no "one size fits all" solutions for patients with a particular diagnosis in practice, which should be treated depends on patient's genetic, environmental, lifestyle choices and so on. Precision medicine can provide personalized treatment for a particular patient that has been drawn more and more attention. There are a large number of treatment options, which is overwhelming for clinicians to make best treatment for a particular patient. One of the effective ways to alleviate this problem is biomedical information retrieval system, which can automatically find out relevant information and proper treatment from mass of alternative treatments and cases. However, in the biomedical literature and clinical trials, there is a larger number of synonymous, polysemous and context terms, causing the semantic gap between query and document in traditional biomedical information retrieval systems. Zuoxi Yang |
SIGIR | 1 |
| 2020 | HAGERec: Hierarchical Attention Graph Convolutional Network Incorporating Knowledge Graph for Explainable Recommendation
Zuoxi Yang, Shoubin Dong |
Knowl. Based Syst. | 1 |