EDBT 2026 Demo / reviewers in the wild / expert
Qinyuan Su
dblp:242/5148
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 50% Web and social media mining · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Smart cities and intelligent transportation · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and social media mining
user-generated content |
0.4 | 1 | 2019 | PerRD: A System for Personalized Route Description · ICDE 2019 |
Smart cities and intelligent transportation › navigation
vehicle navigation |
0.1 | 1 | 2019 | PerRD: A System for Personalized Route Description · ICDE 2019 |
Methods — techniques the papers use, named apart from their topics
path optimization · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | PerRD: A System for Personalized Route DescriptionabstractNowadays, mobile devices are already seen everywhere in life, which makes the application of vehicle navigation more and more widely. The traditional turn-by-turn navigation does the path planning just based on the characteristics of the roads themselves, and then gives mechanized steering instructions at each corner. For those roads people are familiar with in this route, path descriptions which provide detailed route description information, will become redundant and verbose. In this paper, we study a Personalized Route Description system dubbed PerRD - with which the goal is to generate more customized and intuitive route descriptions based on user generated content. The goal is to optimize a given route description with paths which users know well, which makes the route more consistent with users' driving habits, and to create a concise and meaningful route descriptions with POIs and street names. Han Su 0001, Guanglin Cong, Wei Chen 0070, Qinyuan Su, Bolong Zheng, Kai Zheng 0001 |
ICDE | 4 |