EDBT 2026 Demo / reviewers in the wild / expert
Ravi Khadiwala
dblp:116/5161
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
—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 |
Web and social media mining · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and social media mining
event analysis |
0.1 | 1 | 2012 | TEDAS: A Twitter-based Event Detection and Analysis System · ICDE 2012 |
Web and social media mining › event detection
social event detection |
0.1 | 1 | 2012 | TEDAS: A Twitter-based Event Detection and Analysis System · ICDE 2012 |
Methods — techniques the papers use, named apart from their topics
tweet ranking · 0.1tweet crawling · 0.1tweet classification · 0.1location extraction · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | TEDAS: A Twitter-based Event Detection and Analysis SystemabstractWitnessing the emergence of Twitter, we propose a Twitter-based Event Detection and Analysis System (TEDAS), which helps to (1) detect new events, to (2) analyze the spatial and temporal pattern of an event, and to (3) identify importance of events. In this demonstration, we show the overall system architecture, explain in detail the implementation of the components that crawl, classify, and rank tweets and extract location from tweets, and present some interesting results of our system. Rui Li 0049, Kin Hou Lei, Ravi Khadiwala, Kevin Chen-Chuan Chang |
ICDE | 3 |