A Collaborative Network-Based Retrieval Model for Open Source Domain Experts

Qingxi Peng; Zhenjie Weng; Wei Wang; Xinyi Wang; Lan You

doi:10.1109/TBDATA.2024.3524829

A Collaborative Network-Based Retrieval Model for Open Source Domain Experts

Qingxi Peng
, Zhenjie Weng
, Wei Wang^*
, Xinyi Wang
, Lan You

^*Corresponding author for this work

School of Data Science and Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Aiming at the problem that the GitHub platform only supports the retrieval of developers through their usernames and it is difficult to directly obtain developers' expertise information, this paper proposes an open source domain expert retrieval model (OSDERM) based on the network representation learning algorithm OSC2vec (Open Source Collaboration to Vector). The model mainly consists of two core parts: Expert Profiling and Expert Finding. Expert Profiling aims to enrich the expertise information in the search results by labeling the expertise of developers; while Expert Finding achieves rapid location of the most suitable domain experts through keyword matching, which greatly saves the time and effort of searching for experts in the open source community.

Original language	English
Pages (from-to)	1720-1732
Number of pages	13
Journal	IEEE Transactions on Big Data
Volume	11
Issue number	4
DOIs	https://doi.org/10.1109/TBDATA.2024.3524829
State	Published - 2025

Keywords

Open source domain expert
expert retrieval
network representation learning algorithm OSC2vec
open source domain expert retrieval model OSDERM

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10.1109/TBDATA.2024.3524829

Cite this

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title = "A Collaborative Network-Based Retrieval Model for Open Source Domain Experts",

abstract = "Aiming at the problem that the GitHub platform only supports the retrieval of developers through their usernames and it is difficult to directly obtain developers' expertise information, this paper proposes an open source domain expert retrieval model (OSDERM) based on the network representation learning algorithm OSC2vec (Open Source Collaboration to Vector). The model mainly consists of two core parts: Expert Profiling and Expert Finding. Expert Profiling aims to enrich the expertise information in the search results by labeling the expertise of developers; while Expert Finding achieves rapid location of the most suitable domain experts through keyword matching, which greatly saves the time and effort of searching for experts in the open source community.",

keywords = "Open source domain expert, expert retrieval, network representation learning algorithm OSC2vec, open source domain expert retrieval model OSDERM",

author = "Qingxi Peng and Zhenjie Weng and Wei Wang and Xinyi Wang and Lan You",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.",

year = "2025",

doi = "10.1109/TBDATA.2024.3524829",

language = "英语",

volume = "11",

pages = "1720--1732",

journal = "IEEE Transactions on Big Data",

issn = "2332-7790",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - A Collaborative Network-Based Retrieval Model for Open Source Domain Experts

AU - Peng, Qingxi

AU - Weng, Zhenjie

AU - Wang, Wei

AU - Wang, Xinyi

AU - You, Lan

PY - 2025

Y1 - 2025

N2 - Aiming at the problem that the GitHub platform only supports the retrieval of developers through their usernames and it is difficult to directly obtain developers' expertise information, this paper proposes an open source domain expert retrieval model (OSDERM) based on the network representation learning algorithm OSC2vec (Open Source Collaboration to Vector). The model mainly consists of two core parts: Expert Profiling and Expert Finding. Expert Profiling aims to enrich the expertise information in the search results by labeling the expertise of developers; while Expert Finding achieves rapid location of the most suitable domain experts through keyword matching, which greatly saves the time and effort of searching for experts in the open source community.

AB - Aiming at the problem that the GitHub platform only supports the retrieval of developers through their usernames and it is difficult to directly obtain developers' expertise information, this paper proposes an open source domain expert retrieval model (OSDERM) based on the network representation learning algorithm OSC2vec (Open Source Collaboration to Vector). The model mainly consists of two core parts: Expert Profiling and Expert Finding. Expert Profiling aims to enrich the expertise information in the search results by labeling the expertise of developers; while Expert Finding achieves rapid location of the most suitable domain experts through keyword matching, which greatly saves the time and effort of searching for experts in the open source community.

KW - Open source domain expert

KW - expert retrieval

KW - network representation learning algorithm OSC2vec

KW - open source domain expert retrieval model OSDERM

UR - https://www.scopus.com/pages/publications/85214310380

U2 - 10.1109/TBDATA.2024.3524829

DO - 10.1109/TBDATA.2024.3524829

M3 - 文章

AN - SCOPUS:85214310380

SN - 2332-7790

VL - 11

SP - 1720

EP - 1732

JO - IEEE Transactions on Big Data

JF - IEEE Transactions on Big Data

IS - 4

ER -

A Collaborative Network-Based Retrieval Model for Open Source Domain Experts

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Keywords

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