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Tag recommendation for open source software
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AI
DOI：10.1007/s11704-013-2394-x.png)
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摘要
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Nowadays open source software becomes highly popular and is of great importance for most software engineering activities. To facilitate software organization and retrieval, tagging is extensively used in open source communities. However, finding the desired software through tags in these communities such as Freecode and ohloh is still challenging because of tag insufficiency. In this paper, we propose TRG (tag recommendation based on semantic graph), a novel approach to discovering and enriching tags of open source software. Firstly, we propose a semantic graph to model the semantic correlations between tags and the words in software descriptions. Then based on the graph, we design an effective algorithm to recommend tags for software. With comprehensive experiments on large-scale open source software datasets by comparing with several typical related works, we demonstrate the effectiveness and efficiency of our method in recommending proper tags.
Keyword:
open source software
semantic graph
tag recommendation
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4.6
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1.6K
被引数:
2.8K
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