PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models

PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models

Stack Overflow is often viewed as one of the most influential Software Question & Answer (SQA) websites, containing millions of programming-related questions and answers. Tags play a critical role in efficiently structuring the contents in Stack Overflow and are vital to support a range of site...

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Main Authors: HE, Junda, XU, Bowen, YANG, Zhou, HAN, DongGyun, YANG, Chengran, LO, David
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
Tag Recommendation
Transformer
Pre-Trained Models
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/7689
https://ink.library.smu.edu.sg/context/sis_research/article/8692/viewcontent/PTM.pdf
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Institution: Singapore Management University
Language: English
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spelling sg-smu-ink.sis_research-86922023-10-10T06:44:43Z PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models HE, Junda XU, Bowen YANG, Zhou HAN, DongGyun YANG, Chengran LO, David Stack Overflow is often viewed as one of the most influential Software Question & Answer (SQA) websites, containing millions of programming-related questions and answers. Tags play a critical role in efficiently structuring the contents in Stack Overflow and are vital to support a range of site operations, e.g., querying relevant contents. Poorly selected tags often introduce extra noise and redundancy, which raises problems like tag synonym and tag explosion. Thus, an automated tag recommendation technique that can accurately recommend high-quality tags is desired to alleviate the problems mentioned above. 2022-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7689 info:doi/10.1145/3524610.3527897 https://ink.library.smu.edu.sg/context/sis_research/article/8692/viewcontent/PTM.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Tag Recommendation Transformer Pre-Trained Models Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Tag Recommendation
Transformer
Pre-Trained Models
Software Engineering
spellingShingle Tag Recommendation
Transformer
Pre-Trained Models
Software Engineering
HE, Junda
XU, Bowen
YANG, Zhou
HAN, DongGyun
YANG, Chengran
LO, David
PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models
description Stack Overflow is often viewed as one of the most influential Software Question & Answer (SQA) websites, containing millions of programming-related questions and answers. Tags play a critical role in efficiently structuring the contents in Stack Overflow and are vital to support a range of site operations, e.g., querying relevant contents. Poorly selected tags often introduce extra noise and redundancy, which raises problems like tag synonym and tag explosion. Thus, an automated tag recommendation technique that can accurately recommend high-quality tags is desired to alleviate the problems mentioned above.
format text
author HE, Junda
XU, Bowen
YANG, Zhou
HAN, DongGyun
YANG, Chengran
LO, David
author_facet HE, Junda
XU, Bowen
YANG, Zhou
HAN, DongGyun
YANG, Chengran
LO, David
author_sort HE, Junda
title PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models
title_short PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models
title_full PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models
title_fullStr PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models
title_full_unstemmed PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models
title_sort ptm4tag: sharpening tag recommendation of stack overflow posts with pre-trained models
publisher Institutional Knowledge at Singapore Management University
publishDate 2022
url https://ink.library.smu.edu.sg/sis_research/7689
https://ink.library.smu.edu.sg/context/sis_research/article/8692/viewcontent/PTM.pdf
_version_ 1781793932102860800

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