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Zhaoting Su

dblp:222/3650 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2

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%
Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and social media mining › social media analysis › user identification
cross-platform user identification		 0.312018
A Comment on "Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks" · IEEE Trans. Knowl. Data Eng. 2018
Web and social media mining › social media analysis
user identification		 0.312018
A Comment on "Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks" · IEEE Trans. Knowl. Data Eng. 2018
Graph algorithms and graph theory
graph matching		 0.112018
A Comment on "Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks" · IEEE Trans. Knowl. Data Eng. 2018

Methods — techniques the papers use, named apart from their topics

seed user matched pairs · 0.7friend relationship-based user identification · 0.7
YearPublicationVenuePosition
2020 Exploiting similarities of user friendship networks across social networks for user identification
Yongjun Li 0006, Zhaoting Su, Jiaqi Yang 0003, Congjie Gao
 Inf. Sci.2
2018 A Comment on "Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks"
abstract
The Friend Relationship-Based User Identification (FRUI) algorithm is considered to be the ideal method. However, if the seed User Matched Pairs (UMPs) were not suitable, FRUI would stop early due to Controversial UMPs. We highlight this gap and propose a minor change to make FRUI a more general identification algorithm.
Yongjun Li 0006, Zhaoting Su
 IEEE Trans. Knowl. Data Eng.2