activity
20172026
most citedKnowledge-guided Deep Reinforcement Learning for Interactive Recommendation

42 citations · 62 across the 34 of their papers we have counts for

collaborators
Showing cs.DBShow all

11 papers · 1 filter

cs.DB2026

Algebraic Subgraph Counting

Qiuyu Guo, Jianye Yang, Wenjie Zhang +3

Subgraph isomorphism counting is a fundamental problem in graph analytics, which aims to find the number of subgraph isomorphisms of a query graph in a data graph. The candidate tr…

cs.DB2026

Efficient Approximate Nearest Neighbor Search under Multi-Attribute Range Filter

Yuanhang Yu, Dawei Cheng, Ying Zhang +3

Nearest neighbor search on high-dimensional vectors is fundamental in modern AI and database systems. In many real-world applications, queries involve constraints on multiple numer…

cs.DB2026

RLMiner: Finding the Most Frequent k-sized Subgraph via Reinforcement Learning

Wei Huang, Hanchen Wang, Dong Wen +4

Identifying the most frequent induced subgraph of size in a target graph is a fundamental graph mining problem with direct implications for Web-related data mining and social n…

cs.DB2025

Accelerating Historical K-Core Search in Temporal Graphs

Zhuo Ma, Dong Wen, Kaiyu Chen +3

We study the temporal k-core component search (TCCS), which outputs the k-core containing the query vertex in the snapshot over an arbitrary query time window in a temporal graph.…

cs.DB2025

Accelerating K-Core Computation in Temporal Graphs

Zhuo Ma, Dong Wen, Hanchen Wang +3

We address the problem of enumerating all temporal k-cores given a query time range and a temporal graph, which suffers from poor efficiency and scalability in the state-of-the-art…

cs.DB2024

Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs

Long Yuan, Kongzhang Hao, Xuemin Lin +1

Hop-constrained s-t simple path (HC-s-t path) enumeration is a fundamental problem in graph analysis. Existing solutions for this problem focus on optimizing the processing perform…

cs.DB2023

High-Ratio Compression for Machine-Generated Data

Jiujing Zhang, Zhitao Shen, Shiyu Yang +7

Machine-generated data is rapidly growing and poses challenges for data-intensive systems, especially as the growth of data outpaces the growth of storage space. To cope with the s…

cs.DB2021★ 3 cited

HUGE: An Efficient and Scalable Subgraph Enumeration System

Zhengyi Yang, Longbin Lai, Xuemin Lin +2

Subgraph enumeration is a fundamental problem in graph analytics, which aims to find all instances of a given query graph on a large data graph. In this paper, we propose a system…

cs.DB2020

PEFP: Efficient k-hop Constrained s-t Simple Path Enumeration on FPGA

Zhengmin Lai, You Peng, Shiyu Yang +2

Graph plays a vital role in representing entities and their relationships in a variety of fields, such as e-commerce networks, social networks and biological networks. Given two ve…

cs.DB2020★ 1 cited

AOT: Pushing the Efficiency Boundary of Main-memory Triangle Listing

Michael Yu, Lu Qin, Ying Zhang +2

Triangle listing is an important topic significant in many practical applications. Efficient algorithms exist for the task of triangle listing. Recent algorithms leverage an orient…

cs.DB2020★ 4 cited

Efficient Bitruss Decomposition for Large-scale Bipartite Graphs

Kai Wang, Xuemin Lin, Lu Qin +2

Cohesive subgraph mining in bipartite graphs becomes a popular research topic recently. An important structure k-bitruss is the maximal cohesive subgraph where each edge is contain…