Computer Science ›› 2020, Vol. 47 ›› Issue (12): 56-64.doi: 10.11896/jsjkx.201200031
Special Issue: Software Engineering & Requirements Engineering for Complex Systems
Previous Articles Next Articles
WANG Ying, ZHENG Li-wei, ZHANG Yu-yao, ZHANG Xiao-yun
CLC Number:
| [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. |
| [1] | LENG Dian-dian, DU Peng, CHEN Jian-ting, XIANG Yang. Automated Container Terminal Oriented Travel Time Estimation of AGV [J]. Computer Science, 2022, 49(9): 208-214. |
| [2] | NING Han-yang, MA Miao, YANG Bo, LIU Shi-chang. Research Progress and Analysis on Intelligent Cryptology [J]. Computer Science, 2022, 49(9): 288-296. |
| [3] | HE Qiang, YIN Zhen-yu, HUANG Min, WANG Xing-wei, WANG Yuan-tian, CUI Shuo, ZHAO Yong. Survey of Influence Analysis of Evolutionary Network Based on Big Data [J]. Computer Science, 2022, 49(8): 1-11. |
| [4] | LI Yao, LI Tao, LI Qi-fan, LIANG Jia-rui, Ibegbu Nnamdi JULIAN, CHEN Jun-jie, GUO Hao. Construction and Multi-feature Fusion Classification Research Based on Multi-scale Sparse Brain Functional Hyper-network [J]. Computer Science, 2022, 49(8): 257-266. |
| [5] | ZHANG Guang-hua, GAO Tian-jiao, CHEN Zhen-guo, YU Nai-wen. Study on Malware Classification Based on N-Gram Static Analysis Technology [J]. Computer Science, 2022, 49(8): 336-343. |
| [6] | CHEN Ming-xin, ZHANG Jun-bo, LI Tian-rui. Survey on Attacks and Defenses in Federated Learning [J]. Computer Science, 2022, 49(7): 310-323. |
| [7] | LI Ya-ru, ZHANG Yu-lai, WANG Jia-chen. Survey on Bayesian Optimization Methods for Hyper-parameter Tuning [J]. Computer Science, 2022, 49(6A): 86-92. |
| [8] | ZHAO Lu, YUAN Li-ming, HAO Kun. Review of Multi-instance Learning Algorithms [J]. Computer Science, 2022, 49(6A): 93-99. |
| [9] | WANG Fei, HUANG Tao, YANG Ye. Study on Machine Learning Algorithms for Life Prediction of IGBT Devices Based on Stacking Multi-model Fusion [J]. Computer Science, 2022, 49(6A): 784-789. |
| [10] | XIAO Zhi-hong, HAN Ye-tong, ZOU Yong-pan. Study on Activity Recognition Based on Multi-source Data and Logical Reasoning [J]. Computer Science, 2022, 49(6A): 397-406. |
| [11] | YAO Ye, ZHU Yi-an, QIAN Liang, JIA Yao, ZHANG Li-xiang, LIU Rui-liang. Android Malware Detection Method Based on Heterogeneous Model Fusion [J]. Computer Science, 2022, 49(6A): 508-515. |
| [12] | XU Jie, ZHU Yu-kun, XING Chun-xiao. Application of Machine Learning in Financial Asset Pricing:A Review [J]. Computer Science, 2022, 49(6): 276-286. |
| [13] | YAO Xiao-ming, DING Shi-chang, ZHAO Tao, HUANG Hong, LUO Jar-der, FU Xiao-ming. Big Data-driven Based Socioeconomic Status Analysis:A Survey [J]. Computer Science, 2022, 49(4): 80-87. |
| [14] | LI Ye, CHEN Song-can. Physics-informed Neural Networks:Recent Advances and Prospects [J]. Computer Science, 2022, 49(4): 254-262. |
| [15] | ZHANG Xiao-qing, FANG Jian-sheng, XIAO Zun-jie, CHEN Bang, Risa HIGASHITA, CHEN Wan, YUAN Jin, LIU Jiang. Classification Algorithm of Nuclear Cataract Based on Anterior Segment Coherence Tomography Image [J]. Computer Science, 2022, 49(3): 204-210. |
|
||
Home