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researcher

T. Tran

4 papers hereh-index 161.1k citations67 works total

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

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.IR2
  • cs.AI1
  • cs.SE1
same name
  • T. Tran — 61 papers, h 41
  • T. Tran — 16 papers, h 46
  • T. Tran — 9 papers, h 6
  • T. Tran — 9 papers, h 12
  • T. Tran — 9 papers, h 11
  • T. Tran — 8 papers

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

most citedAn Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration

14 citations · 21 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2021

Configuring Multiple Instances with Multi-Configuration

Alexander Felfernig, Andrei Popescu, Mathias Uta +5

Configuration is a successful application area of Artificial Intelligence. In the majority of the cases, configuration systems focus on configuring one solution (configuration) tha…

cs.IR2021★ 2 cited

Designing Explanations for Group Recommender Systems

A. Felfernig, N. Tintarev, T. N. T. Trang +1

Explanations are used in recommender systems for various reasons. Users have to be supported in making (high-quality) decisions more quickly. Developers of recommender systems want…

cs.IR2021★ 14 cited

An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration

Alexander Felfernig, Viet-Man Le, Andrei Popescu +3

Recommender systems support decisions in various domains ranging from simple items such as books and movies to more complex items such as financial services, telecommunication equi…

cs.SE2021★ 5 cited

DirectDebug: Automated Testing and Debugging of Feature Models

Viet-Man Le, Alexander Felfernig, Mathias Uta +3

Variability models (e.g., feature models) are a common way for the representation of variabilities and commonalities of software artifacts. Such models can be translated to a logic…

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