一种基于重叠社区发现的软件特征提取方法

doi:10.11896/jsjkx.181001856

摘要/Abstract

摘要： 近年来从软件产品的文本描述中提取软件特征获得了大量关注。考虑到产品文本描述中的句子能够更加清晰地表达一个特征的含义,并且文本描述中的每个句子可能会涉及多个软件特征,文中提出了一种通过发现软件产品文本描述中重叠的句子聚簇来提取软件特征的方法。基于复杂网络中的LMF重叠社区发现算法,所提方法通过自定义文本描述中句子之间的相识性度量,构建句子之间的相似性网络,然后发现句子相似性网络中的句子社区,实现对句子的聚类。每个句子社区蕴含一个软件特征,包含了所有潜在描述该软件特征的文本句子。所发现的句子社区可能存在重叠的句子,这些重叠句子同时涉及多个句子社区所蕴含的软件特征。进一步,为了帮助人们更好地理解句子社区所蕴含的特征,所提方法设计了相应的算法来从所有句子社区中依次选择熵最小的社区,并从所选社区中挑选最有代表性的、且其他社区还未选择的句子来作为一个社区所蕴含特征的描述符。文中爬取Softpedia.com网站的软件产品文本描述信息作为实验数据。实验结果表明,所提方法与现有代表性方法相比在准确性与时间方面具有更好的表现。

关键词: 特征提取, 重叠社区发现, 自然语言

Abstract: Extracting software features from natural language of product descriptions has gained a lot of attentions in recent years.In light that the sentences in the descriptions can describe the semantics of software features more precisely and one sentence may be concerned about more than one software feature,this paper proposed a feature identification method by detecting the overlapping clusters of these sentences in the natural language descriptions.Based on the overlapping community detection algorithm (LMF),the proposed method defines a metric to measure the similarity between each pair of sentences in the descriptions,builds a sentence similarity network accordingly,and then detects the overlapping sentence communities in such network.Each sentence community is a cluster which implies one software feature,and contains all the sentences potentially describing the implied feature.Further,in order to help people better understand the characteristics of sentence communities,the proposed method designs corresponding algorithms to select the communities with the lowest entropy from all sentence communities in turn,and to select the most representative sentences from the selected communities that have not been selected by other communities as descriptors of the features contained in the community.The natural language product descriptions from Soft pedia.com were crawled as experimental data.Experimental results show that the proposed method has better performance in accuracy and time consumption.

Key words: Feature extraction, Natural language, Overlapping community detection

中图分类号:

TP311

刘春, 张国良. 一种基于重叠社区发现的软件特征提取方法[J]. 计算机科学, 2019, 46(12): 201-207. https://doi.org/10.11896/jsjkx.181001856

LIU Chun, ZHANG Guo-liang. Software Feature Extraction Method Based on Overlapping Community Detection[J]. Computer Science, 2019, 46(12): 201-207. https://doi.org/10.11896/jsjkx.181001856

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