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20152023
most citedMulti-View Spectral Clustering via Structured Low-Rank Matrix Factorization

433 citations · 968 across the 48 of their papers we have counts for

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Showing 2017Show all

6 papers · 1 filter

cs.DB2017★ 4 cited

An Optimal and Progressive Approach to Online Search of Top-k Influential Communities

Fei Bi, Lijun Chang, Xuemin Lin +1

Community search over large graphs is a fundamental problem in graph analysis. Recent studies propose to compute top-k influential communities, where each reported community not on…

cs.DB2017

Dynamical SimRank Search on Time-Varying Networks

Weiren Yu, Xuemin Lin, Wenjie Zhang +1

In this article, we study the efficient dynamical computation of all-pairs SimRanks on time-varying graphs. Li {\em et al}.'s approach requires time and m…

cs.DB2017

Efficient Graph Edit Distance Computation and Verification via Anchor-aware Lower Bound Estimation

Lijun Chang, Xing Feng, Xuemin Lin +2

Graph edit distance (GED) is an important similarity measure adopted in a similarity-based analysis between two graphs, and computing GED is a primitive operator in graph database…

cs.CV2017★ 433 cited

Multi-View Spectral Clustering via Structured Low-Rank Matrix Factorization

Yang Wang, Lin Wu

Multi-view data clustering attracts more attention than their single view counterparts due to the fact that leveraging multiple independent and complementary information from multi…

cs.DB2017★ 4 cited

Enumerating k-Vertex Connected Components in Large Graphs

Dong Wen, Lu Qin, Xuemin Lin +2

Cohesive subgraph detection is an important graph problem that is widely applied in many application domains, such as social community detection, network visualization, and network…

cs.CV2017★ 190 cited

Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval

Yang Wang, Xuemin Lin, Lin Wu +1

Given a query photo issued by a user (q-user), the landmark retrieval is to return a set of photos with their landmarks similar to those of the query, while the existing studies on…