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Qiang Huang

Harbin Institute of Technology (Shenzhen)

5 papers hereh-index 14792 citations50 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.DB3
  • cs.CL1
  • cs.CV1
affiliations
  • Harbin Institute of Technology (Shenzhen)
Homepage
same name
  • Qiang Huang — 12 papers, h 16
  • Qiang Huang — 5 papers
  • Qiang Huang — 2 papers
  • Qiang Huang — 2 papers, h 4
  • Qiang Huang — 2 papers
  • Qiang Huang — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedLocality-Sensitive Hashing Scheme based on Longest Circular Co-Substring

3 citations · 7 across the 5 of their papers we have counts for

collaborators

4 papers

cs.DB2022

DIOT: Detecting Implicit Obstacles from Trajectories

Yifan Lei, Qiang Huang, Mohan Kankanhalli +1

In this paper, we study a new data mining problem of obstacle detection from trajectory data. Intuitively, given two kinds of trajectories, i.e., reference and query trajectories,…

cs.CV2021

Unsupervised Abstract Reasoning for Raven's Problem Matrices

Tao Zhuo, Qiang Huang, Mohan Kankanhalli

Raven's Progressive Matrices (RPM) is highly correlated with human intelligence, and it has been widely used to measure the abstract reasoning ability of humans. In this paper, to…

cs.DB2021★ 2 cited

A Generic Distributed Clustering Framework for Massive Data

Pingyi Luo, Qiang Huang, Anthony K. H. Tung

In this paper, we introduce a novel Generic distributEd clustEring frameworK (GEEK) beyond k-means clustering to process massive amounts of data. To deal with different data type…

cs.DB2020★ 3 cited

Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring

Yifan Lei, Qiang Huang, Mohan Kankanhalli +1

Locality-Sensitive Hashing (LSH) is one of the most popular methods for c-Approximate Nearest Neighbor Search (c-ANNS) in high-dimensional spaces. In this paper, we propose a n…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.