Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging

Millions of people, including those in the software engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is...

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Main Authors: WANG, Shaowei, LO, David, JIANG, Lingxiao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/sis_research/1578
http://dx.doi.org/10.1109/ICSM.2012.6405332
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spelling sg-smu-ink.sis_research-25772017-04-20T01:25:03Z Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging WANG, Shaowei LO, David JIANG, Lingxiao Millions of people, including those in the software engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is stored in these microblogs. However, microblogs also contain a large amount of noisy content that are less relevant to software developers in engineering software systems. In this work, we perform a preliminary study to investigate the feasibility of automatic classification of microblogs into two categories: relevant and irrelevant to engineering software systems. We extract features from the textual content of the microblogs and the titles of any URLs mentioned in the microblogs. These features are then used to learn a discriminative model used in classifying relevant and irrelevant microblogs. We show that our trained model can achieve a promising classification performance. 2012-09-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/1578 info:doi/10.1109/ICSM.2012.6405332 http://dx.doi.org/10.1109/ICSM.2012.6405332 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Bug reports Collaborative tagging Engineering community Exact matching Feature location Semantic similarity Semantic taxonomies Similarity metrics Software products Software project User study Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Bug reports
Collaborative tagging
Engineering community
Exact matching
Feature location
Semantic similarity
Semantic taxonomies
Similarity metrics
Software products
Software project
User study
Software Engineering
spellingShingle Bug reports
Collaborative tagging
Engineering community
Exact matching
Feature location
Semantic similarity
Semantic taxonomies
Similarity metrics
Software products
Software project
User study
Software Engineering
WANG, Shaowei
LO, David
JIANG, Lingxiao
Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging
description Millions of people, including those in the software engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is stored in these microblogs. However, microblogs also contain a large amount of noisy content that are less relevant to software developers in engineering software systems. In this work, we perform a preliminary study to investigate the feasibility of automatic classification of microblogs into two categories: relevant and irrelevant to engineering software systems. We extract features from the textual content of the microblogs and the titles of any URLs mentioned in the microblogs. These features are then used to learn a discriminative model used in classifying relevant and irrelevant microblogs. We show that our trained model can achieve a promising classification performance.
format text
author WANG, Shaowei
LO, David
JIANG, Lingxiao
author_facet WANG, Shaowei
LO, David
JIANG, Lingxiao
author_sort WANG, Shaowei
title Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging
title_short Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging
title_full Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging
title_fullStr Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging
title_full_unstemmed Inferring Semantically Related Software Terms and their Taxonomy by Leveraging Collaborative Tagging
title_sort inferring semantically related software terms and their taxonomy by leveraging collaborative tagging
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/1578
http://dx.doi.org/10.1109/ICSM.2012.6405332
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