Demo Data from VLDB 2026 / reviewers in the wild / expert
Caroline Lo
dblp:183/9930
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author
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
1 paper |
Web and social media mining · 56% Recommender systems · 44% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and social media mining
user behavior analysis |
0.2 | 1 | 2016 | Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest · KDD 2016 |
Web and social media mining › user behavior analysis
user behavior modeling |
0.1 | 1 | 2016 | Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest · KDD 2016 |
Methods — techniques the papers use, named apart from their topics
case study · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Understanding Behaviors that Lead to Purchasing: A Case Study of PinterestabstractOnline e-commerce applications are becoming a primary vehicle for people to find, compare, and ultimately purchase products. One of the fundamental questions that arises in e-commerce is to characterize, understand, and model user long-term purchasing intent, which is important as it allows for personalized and context relevant e-commerce services. Caroline Lo, Dan Frankowski, Jure Leskovec |
KDD | 1 |