计算机科学 ›› 2020, Vol. 47 ›› Issue (12): 56-64.doi: 10.11896/jsjkx.201200031
所属专题: 复杂系统的软件工程和需求工程
王莹, 郑丽伟, 张禹尧, 张晓妘
WANG Ying, ZHENG Li-wei, ZHANG Yu-yao, ZHANG Xiao-yun
摘要: 从APP用户反馈数据中挖掘用户需求是APP迭代更新和需求获取的一种重要方式用户在APP应用市场中发表对APP不同维度的评价其中蕴含着用户对APP软件的改善需求.但是目前用户反馈数据存在数量大、质量良莠不齐的状况如何从海量的用户评论数据中省时省力地挖掘出有价值的需求具有重要的研究与现实意义.文中着眼于APP开发问题选取360手机助手中的APP用户评论数据旨在挖掘蕴含于用户评论数据中的软件需求.首先从功能性需求与非功能性需求两个维度出发将APP用户评论数据中蕴含的软件需求划分为功能待添加、功能待改进、性能、可用性、可靠性5个需求类别;其次对用户评论进行数据采集、标注构建APP评论需求挖掘数据集;最后利用构建好的数据集进行模型训练与交叉验证探究主流深度学习方法相较于统计机器学习模型在该任务上的表现.实验表明采用的深度学习模型TextCNNText RNN和Transformer相比传统的统计机器学习模型在此任务上更具优势.
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[1] SARRO F,HARMNA M,JIA Y,et al.Customer rating reactions can be predicted purely using app features[C]//Proc of the 26th Requirements Engineering Conference.IEEE,2018. [2] SHI L,CHEN C,WANG Q,et al.Understanding feature requests by leveraging fuzzy method and linguistic[C]//Proc of the 32th IEEE/ACM International Conference on Automated SoftwareEngineering (ASE).2017:440-450. [3] PALOMBA F,SALZA P,CIURUMELEA A,et al.Recommending and localizing change requests for mobile apps based on user reviews[C]//Proc of the 39th International Conference on Software Engineering.USA:IEEE,2017:106-117. [4] SORBO A DI,PANICHELLA S,ALEXANDRU C V,et al.What would users change in my app? summarizing app reviews for recommending software changes[C]//Proc of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering.USA,ACM,2016:499-510. [5] JIANG W,ZHANG L,DAI Y,et al.Analyzing Helpfulness of Online Reviews for User Requirements Elicitation[J].Chinese Journal of Computers,2013,36(1):119-131. [6] SCHNEIDER K.Focusing spontaneous feedback to support system evolution[C]//Proc of the 11th Requirements Engineering Conference.IEEE,2011:165-174. [7] IACOB C,HARRISON R.Retrieving and analyzing mobile apps feature requests from online reviews[C]//Proc of the 10th Working Conference on Mining Software Repositories (MSR).San Francisco,2013:41-44. [8] CHEN N,LIN J,HOI S C H,et al.AR-miner:mining informative reviews for developers from mobile app marketplace[C]//International Conference on Software Engineering.ACM,2014. [9] KHAN J A,XIE Y,LIU L,et al.Analysis of Requirements-Related Arguments in User Forums[C]//Proc of the 27th IEEE International Requirements Engineering Conference (RE).Jeju Island,Korea (South),2019:63-74. [10] KHAN J A,LIU L,JIA Y,et al.Linguistic Analysis of Crowd Requirements:An experimental study[C]//Proc of the RE Workshop.Empri,2018. [11] MAALEJ W,NAYEBI M,JOHANN T,et al.Toward data-dri-ven requirements engineering[J].IEEE Software,2016,33(1):48-54. [12] HOUMB S H,ISLAM S,KNAUSS E,et al.Eliciting securityrequirements and tracing them to design:an integration of Common Criteria,heuristics,and UMLsec[J].Requirements Engineering,2010,15(1):63-93. [13] MAALEJ W,NABIL H.Bug report,feature request,or simply praise? On automatically classifying app reviews[C]//Proc of the 23rd IEEE International Requirements Engineering Confe-rence (RE).Ottawa,ON,2015:116-125. [14] PANICHELLA S,SOEBO A D,GUZMAN E,et al.How Can I Improve My App? Classifying User Reviews for Software Maintenance and Evolution[C]//International Conference on Software Maintenance &Evolution.IEEE,2015. [15] VILLARROEL L,BAVOTA G,RUSSO B,et al.Release Planning of Mobile Apps Based on User Reviews[C]//Proc of the 38th IEEE/ACM International Conference on Software Engineering (ICSE).Austin,TX,2016:14-24. [16] PANICHELLA S,SORBO DI A,GUZMAN E,et al.ARdoc:app reviews development oriented classifier[C]//Acm Sigsoft International Symposium on Foundations of Software Engineering.ACM,2016:1023-1027. [17] SUPRAYOGI E,BUDI I,MAHENDRA R.Information Extraction for Mobile Application User Review[C]//Proc of International Conference on Advanced Computer Science and Information Systems (ICACSIS).Yogyakarta,2018:343-348. [18] BUCHAN J,BANO M,ZOWGHI D,et al.Semi-Automated Extraction of New Requirements from Online Reviews for Software Product Evolution[C]//Proc of the 25th Australasian Software Engineering Conference (ASWEC).Adelaide,SA,2018:31-40. [19] CHEN Q,ZHANG L,JIANG J,et al.Review Analysis Method Based on Support Vector Machine and Latent Dirichlet Allocation[J].Journal of Software,2019,30(5):349-362. [20] HU T Y,JIANG Y.Mining of User's Comments Reflecting Usa-ge Feedback for APP Software[J].Journal of Software,2019(10):3168-3185. [21] ZHANG H F.Introduction to Software Engineering[M].Beijing:Tsinghua University Press. [22] CLELAND-HUANG J,SETTIMI R,ZOU X,et al.The Detection and Classification of Non-Functional Requirements with Application to Early Aspects[C]//Proc of the14th IEEE International Requirements Engineering Conference (RE'06).Minneapolis/St:Paul,MN,2006:39-48. [23] GLINZ M.On Non-Functional Requirements[C]//Proc of IEEE International Requirements Engineering Conference.IEEE,2005. [24] JIA Y D,LIU L.Recognition and Classification of Non-Func-tional Requirements in Chinese[J].Journal of Software,2019,30(10):3115-3126. [25] DEVLIN J,CHANG M W,LEE K,et al.BERT:Pre-training of Deep Bidirectional Transformers for Language Understanding[C]//Proc of NAACL-HLT (1).2019. [26] KIM Y.Convolutional Neural Networksfor Sentence Classification[C]//Proc of Conferenceon Empirical Methods in Natural Language Processing (EMNLP).2014 [27] LAI S,XU L,LIU K,et al.Recurrent convolutional neural networks for text classification[C]//Proc of the 29th AAAI conference on artificial intelligence.2015. [28] HOCHREITER S,SCHMIDHUBER J.Long short-term memory[J].Neural computation,1997,9(8):1735-1780. [29] CHO K,VAN MERRIENBOER B,GULCEHRE C,et al.Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation[C]//Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP).2014:1724-1734. [30] VASWANI A,SHAZEER N,PARMAR N,et al.Attention isAll you Need[C]//Proc of Neural Information Processing Systems.2017:5998-6008. [31] LEWIS D.Naive (Bayes) at Forty:The independence assumption in information retrieval[C]//Proc of European Conference on Machine Learning.Springer,Berlin,Heidelberg,1998. [32] QUINLAN J.C4:5:programs for machine learning[M].Elsevier,2014. [33] CORTES C,VAPNIK V.Support-vector networks[J].Machine Learning,1995,20(3):273-297. [34] BREIMAN L.Random forests[J].Machine Learning,2001,45(1):5-32. [35] Paszke A,GROSS S,MASSA F,et al.Pytorch:An imperative style,high-performance deep learning library[C]//Proc of Advances in Neural Information Processing Systems.2019:8026-8037. [36] KINGMA D P,BA J.Adam:A method for stochastic optimization[C]//Proc of the 3rd International Conference on Learning Representations.2015. [37] ABUALHAIJA S,ARORA C,SABETZADEH M,et al.A Machine Learning-Based Approach for Demarcating Requirements in Textual Specifications[C]//Proc of 27th International Requirements Engineering Conference (RE).IEEE,2019. [38] MIKOLOV T,CHEN K,CORRADO G,et al.Efficient estimation of word representations in vector space[C]//Proc of the 3rd International Conference on Learning Representations.2013. |
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