Automatic Classification of Requirements Based on Convolutional Neural Networks
暂无分享,去创建一个
[1] Daniel Méndez Fernández,et al. It's the Activities, Stupid! A New Perspective on RE Quality , 2015, 2015 IEEE/ACM 2nd International Workshop on Requirements Engineering and Testing.
[2] Lior Rokach,et al. Introduction to Knowledge Discovery and Data Mining , 2010, Data Mining and Knowledge Discovery Handbook.
[3] Jonas Winkler. Automatische Klassifikation von Anforderungen zur Unterstützung von Qualitätssicherungsprozessen , 2016, GI-Jahrestagung.
[4] Hod Lipson,et al. Understanding Neural Networks Through Deep Visualization , 2015, ArXiv.
[5] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[6] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[7] Daniel Ott,et al. Automatic Requirement Categorization of Large Natural Language Specifications at Mercedes-Benz for Review Improvements , 2013, REFSQ.
[8] Anna Perini,et al. A Machine Learning Approach to Software Requirements Prioritization , 2013, IEEE Transactions on Software Engineering.
[9] Phil Blunsom,et al. A Convolutional Neural Network for Modelling Sentences , 2014, ACL.
[10] Charu C. Aggarwal,et al. A Survey of Text Clustering Algorithms , 2012, Mining Text Data.
[11] Charu C. Aggarwal,et al. A Survey of Text Classification Algorithms , 2012, Mining Text Data.
[12] James T. Kwok. Automated Text Categorization Using Support Vector Machine , 1998, ICONIP.
[13] Wenbin Li,et al. Measuring Requirement Quality to Predict Testability , 2015, 2015 IEEE Second International Workshop on Artificial Intelligence for Requirements Engineering (AIRE).
[14] Jane Cleland-Huang,et al. Automated classification of non-functional requirements , 2007, Requirements Engineering.
[15] Ye Zhang,et al. A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification , 2015, IJCNLP.
[16] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[17] José Miguel Mantas,et al. Extraction of similarity based fuzzy rules from artificial neural networks , 2006, Int. J. Approx. Reason..
[18] Nitesh V. Chawla,et al. Data Mining for Imbalanced Datasets: An Overview , 2005, The Data Mining and Knowledge Discovery Handbook.
[19] Vivek Narayanan,et al. Fast and Accurate Sentiment Classification Using an Enhanced Naive Bayes Model , 2013, IDEAL.
[20] Wenbin Li,et al. Weka meets TraceLab: Toward convenient classification: Machine learning for requirements engineering problems: A position paper , 2014, 2014 IEEE 1st International Workshop on Artificial Intelligence for Requirements Engineering (AIRE).
[21] Dan Klein,et al. Accurate Unlexicalized Parsing , 2003, ACL.
[22] Yoon Kim,et al. Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.
[23] Manfred Broy,et al. A meta model for artefact-orientation: fundamentals and lessons learned in requirements engineering , 2010, MODELS'10.
[24] Ignacio Requena,et al. Are artificial neural networks black boxes? , 1997, IEEE Trans. Neural Networks.
[25] Charu C. Aggarwal,et al. Neural Networks and Deep Learning , 2018, Springer International Publishing.