61 citations · 67 across the 5 of their papers we have counts for
9 papers
Voting-based Opinion Maximization
Arkaprava Saha, Xiangyu Ke, Arijit Khan +1
We investigate the novel problem of voting-based opinion maximization in a social network: Find a given number of seed nodes for a target campaigner, in the presence of other compe…
Aggregate Queries on Knowledge Graphs: Fast Approximation with Semantic-aware Sampling
Yuxiang Wang, Arijit Khan, Xiaoliang Xu +3
A knowledge graph (KG) manages large-scale and real-world facts as a big graph in a schema-flexible manner. Aggregate query is a fundamental query over KGs, e.g., "what is the aver…
Maximizing Contrasting Opinions in Signed Social Networks
Kaivalya Rawal, Arijit Khan
The classic influence maximization problem finds a limited number of influential seed users in a social network such that the expected number of influenced users in the network, fo…
Semantic Guided and Response Times Bounded Top-k Similarity Search over Knowledge Graphs
Yuxiang Wang, Arijit Khan, Tianxing Wu +2
Recently, graph query is widely adopted for querying knowledge graphs. Given a query graph , the graph query finds subgraphs in a knowledge graph that exactly or approxima…
Distance-generalized Core Decomposition
Francesco Bonchi, Arijit Khan, Lorenzo Severini
The -core of a graph is defined as the maximal subgraph in which every vertex is connected to at least other vertices within that subgraph. In this work we introduce a dista…
An In-Depth Comparison of s-t Reliability Algorithms over Uncertain Graphs
Xiangyu Ke, Arijit Khan, Leroy Lim Hong Quan
Uncertain, or probabilistic, graphs have been increasingly used to represent noisy linked data in many emerging applications, and have recently attracted the attention of the datab…