A survey towards an integration of big data analytics to big insights for value-creation

[1]  Rahat Iqbal,et al.  Big Data analytics and Computational Intelligence for Cyber-Physical Systems: Recent trends and state of the art applications , 2017, Future Gener. Comput. Syst..

[2]  Five pillars of prescriptive analytics success , 2019, May/June 2013.

[3]  Michail N. Giannakos,et al.  Big data analytics capabilities: a systematic literature review and research agenda , 2017, Information Systems and e-Business Management.

[4]  Ayoub Ait Lahcen,et al.  Big Data technologies: A survey , 2017, J. King Saud Univ. Comput. Inf. Sci..

[5]  Aa Alshehri Ay Ghazwani Ra Darwesh Sa Alzahrani Alotaibi,et al.  Big Data for the Enterprise , 2018 .

[6]  Terry Anthony Byrd,et al.  Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations , 2018 .

[7]  Athanasios V. Vasilakos,et al.  The role of big data analytics in Internet of Things , 2017, Comput. Networks.

[8]  Jharna Majumdar,et al.  Analysis of agriculture data using data mining techniques: application of big data , 2017, Journal of Big Data.

[9]  Fei Jiang,et al.  Big data issues in smart grid – A review , 2017 .

[10]  J. Amankwah‐Amoah,et al.  A multidisciplinary perspective of big data in management research , 2017 .

[11]  Yingfeng Zhang,et al.  A framework for Big Data driven product lifecycle management , 2017 .

[12]  Mansaf Alam,et al.  A survey on scholarly data: From big data perspective , 2017, Inf. Process. Manag..

[13]  Athanasios V. Vasilakos,et al.  Machine learning on big data: Opportunities and challenges , 2017, Neurocomputing.

[14]  S. Wolfert,et al.  Big Data in Smart Farming – A review , 2017 .

[15]  Yurong Liu,et al.  A survey of deep neural network architectures and their applications , 2017, Neurocomputing.

[16]  Lori Bowen Ayre,et al.  Open Data: What It Is and Why You Should Care , 2017, Public Libr. Q..

[17]  Ibrar Yaqoob,et al.  Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges , 2017, IEEE Access.

[18]  Mohamed I. Gomaa,et al.  Toward integration of Big Data, technology and information systems competencies into the accounting curriculum , 2017 .

[19]  Terry Anthony Byrd,et al.  Big data analytics : Understanding its capabilities and potential bene fi ts for healthcare organizations , 2017 .

[20]  Jorge Armando Cortés Ramírez,et al.  The Strategic Business Value of Big Data , 2017 .

[21]  W. Currie,et al.  A model for unpacking big data analytics in high-frequency trading , 2017 .

[22]  Jay Lee,et al.  Predictive Big Data Analytics and Cyber Physical Systems for TES Systems , 2017 .

[23]  Z. Irani,et al.  Critical analysis of Big Data challenges and analytical methods , 2017 .

[24]  Adrian Knapczyk,et al.  Present Trends in Research on Application of Artificial Neural Networks in Agricultural Engineering , 2016 .

[25]  Athanasios V. Vasilakos,et al.  Big data: From beginning to future , 2016, Int. J. Inf. Manag..

[26]  Ying Wah Teh,et al.  Big data reduction framework for value creation in sustainable enterprises , 2016, Int. J. Inf. Manag..

[27]  He Li,et al.  The promising future of healthcare services: When big data analytics meets wearable technology , 2016, Inf. Manag..

[28]  Erdogan Dogdu,et al.  An extended IoT framework with semantics, big data, and analytics , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[29]  Asif Gill,et al.  Towards an IoT Big Data Analytics Framework: Smart Buildings Systems , 2016, 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS).

[30]  Ali Bou Nassif,et al.  Data mining techniques in social media: A survey , 2016, Neurocomputing.

[31]  Benjamin T. Hazen,et al.  Big data and predictive analytics for supply chain sustainability: A theory-driven research agenda , 2016, Comput. Ind. Eng..

[32]  Petri T. Helo,et al.  Big data applications in operations/supply-chain management: A literature review , 2016, Comput. Ind. Eng..

[33]  John S. Edwards,et al.  Using Knowledge Management to Give Context to Analytics and Big Data and Reduce Strategic Risk , 2016 .

[34]  Mario Piattini,et al.  A Data Quality in Use model for Big Data , 2016, Future Gener. Comput. Syst..

[35]  Paolo Giudici,et al.  Big data analysis for financial risk management , 2016, Journal of Big Data.

[36]  Anand Paul,et al.  IoT-based smart city development using big data analytical approach , 2016, 2016 IEEE International Conference on Automatica (ICA-ACCA).

[37]  Dong-Hee Shin,et al.  Demystifying big data: Anatomy of big data developmental process , 2016 .

[38]  Yunhuai Liu,et al.  The big data analytics and applications of the surveillance system using video structured description technology , 2016, Cluster Computing.

[39]  Rick Kazman,et al.  Agile Big Data Analytics for Web-Based Systems: An Architecture-Centric Approach , 2016, IEEE Transactions on Big Data.

[40]  Anil Bilgihan,et al.  Meeting revenue management challenges: Knowledge, skills and abilities , 2016 .

[41]  Ibrar Yaqoob,et al.  A survey of big data management: Taxonomy and state-of-the-art , 2016, J. Netw. Comput. Appl..

[42]  Lukumon O. Oyedele,et al.  Big Data in the construction industry: A review of present status, opportunities, and future trends , 2016, Adv. Eng. Informatics.

[43]  Rajkumar Buyya,et al.  Big Data: Principles and Paradigms , 2016 .

[44]  Nir Kshetri,et al.  Big data's role in expanding access to financial services in China , 2016, Int. J. Inf. Manag..

[45]  Feras Batarseh,et al.  Assessing the Quality of Service Using Big Data Analytics: With Application to Healthcare , 2016, Big Data Res..

[46]  Qihui Wu,et al.  A survey of machine learning for big data processing , 2016, EURASIP Journal on Advances in Signal Processing.

[47]  Ruo-Ping Han,et al.  Disease prediction with different types of neural network classifiers , 2016, Telematics Informatics.

[48]  Jie Li,et al.  Rethinking big data: A review on the data quality and usage issues , 2016 .

[49]  Ravikiran Vatrapu,et al.  Social Set Analysis: A Set Theoretical Approach to Big Data Analytics , 2016, IEEE Access.

[50]  Michael S. Lew,et al.  Deep learning for visual understanding: A review , 2016, Neurocomputing.

[51]  Shanlin Yang,et al.  Big data driven smart energy management: From big data to big insights , 2016 .

[52]  Andrea De Mauro,et al.  A formal definition of Big Data based on its essential features , 2016 .

[53]  Hwee Pink Tan,et al.  Mobile big data analytics using deep learning and apache spark , 2016, IEEE Network.

[54]  Roger H. L. Chiang,et al.  Big Data Research in Information Systems: Toward an Inclusive Research Agenda , 2016, J. Assoc. Inf. Syst..

[55]  Netsanet Haile,et al.  Value creation in software service platforms , 2016, Future Gener. Comput. Syst..

[56]  Rajkumar Buyya,et al.  Big Data Analytics = Machine Learning + Cloud Computing , 2016, ArXiv.

[57]  Peter C. Verhoef,et al.  Creating Value with Big Data Analytics: Making Smarter Marketing Decisions , 2016 .

[58]  I. A. Hashem,et al.  A survey of big data management : Taxonomy and state-ofthe-art , 2016 .

[59]  Wenhuan Lu,et al.  Implementing Big Data Analytics Projects in Business , 2016 .

[60]  Ravindra C. Thool,et al.  Big Data in Precision Agriculture Through ICT: Rainfall Prediction Using Neural Network Approach , 2016 .

[61]  L. Padma Suresh,et al.  Proceedings of the International Conference on Soft Computing Systems , 2016 .

[62]  Nandini S. Sidnal,et al.  Big Data and Analytics—A Journey Through Basic Concepts to Research Issues , 2016 .

[63]  Pradeepini Gera,et al.  A Recent Study of Emerging Tools and Technologies Boosting Big Data Analytics , 2016 .

[64]  Tilman Becker,et al.  Big Data Usage , 2016, New Horizons for a Data-Driven Economy.

[65]  Michal Tkác,et al.  Artificial neural networks in business: Two decades of research , 2016, Appl. Soft Comput..

[66]  Pengtao Xie,et al.  Strategies and Principles of Distributed Machine Learning on Big Data , 2015, ArXiv.

[67]  Gang Lu,et al.  Latency critical big data computing in finance , 2015 .

[68]  Daniel Pakkala,et al.  Reference Architecture and Classification of Technologies, Products and Services for Big Data Systems , 2015, Big Data Res..

[69]  Jameela Al-Jaroodi,et al.  Applications of big data to smart cities , 2015, Journal of Internet Services and Applications.

[70]  Tom Hänel,et al.  Linking Operational Business Intelligence with Value-Based Business Requirements , 2015, I3E.

[71]  Athanasios V. Vasilakos,et al.  Big data analytics: a survey , 2015, Journal of Big Data.

[72]  Gabriel Ordonez-Plata,et al.  Towards a smart city: Design of a domestic smart grid , 2015, 2015 IEEE PES Innovative Smart Grid Technologies Latin America (ISGT LATAM).

[73]  Yao Hu,et al.  Design of a web-based application of the coupled multi-agent system model and environmental model for watershed management analysis using Hadoop , 2015, Environ. Model. Softw..

[74]  Andreas Tolk,et al.  The next generation of modeling & simulation: integrating big data and deep learning , 2015, SummerSim.

[75]  Yi-Ting Chen,et al.  Generalized Optimal Wavelet Decomposing Algorithm for Big Financial Data , 2015 .

[76]  Sule Balkan,et al.  Video Analytics in Market Research , 2015, Inf. Syst. Manag..

[77]  Abhishek Sharma,et al.  Augmenting Data Warehouses with Big Data , 2015, Inf. Syst. Manag..

[78]  N. F Xie,et al.  Research on Big Data Technology-Based Agricultural Information System , 2015 .

[79]  Roman Chychyla,et al.  Big Data Analytics in Financial Statement Audits , 2015 .

[80]  A. Kogan,et al.  Big Data in Accounting: An Overview , 2015 .

[81]  Yu Liu,et al.  DeepIndex for Accurate and Efficient Image Retrieval , 2015, ICMR.

[82]  Muhammad Younas,et al.  Emerging trends and technologies in big data processing , 2015, Concurr. Comput. Pract. Exp..

[83]  Benjamin W. Wah,et al.  Significance and Challenges of Big Data Research , 2015, Big Data Res..

[84]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[85]  Shahriar Akter,et al.  How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study , 2015 .

[86]  Jack Hagel.  Bringing Analytics to Life , 2015 .

[87]  Guang-Bin Huang,et al.  Trends in extreme learning machines: A review , 2015, Neural Networks.

[88]  R H Dolin,et al.  Health Level Seven Interoperability Strategy: Big Data, Incrementally Structured , 2014, Methods of Information in Medicine.

[89]  Rajkumar Buyya,et al.  Big Data computing and clouds: Trends and future directions , 2013, J. Parallel Distributed Comput..

[90]  Shang Xiang,et al.  Data Quality, Analytics, and Privacy in Big Data , 2015 .

[91]  Mikel Niño,et al.  ENTENDIENDO EL BIG DATA: ANTECEDENTES, ORIGEN Y DESARROLLO POSTERIOR , 2015 .

[92]  Alexey Cheptsov,et al.  Leveraging High-Performance Computing Infrastructures to Web Data Analytic Applications by Means of Message-Passing Interface , 2015 .

[93]  E. A. Mary Anita,et al.  A Survey of Big Data Analytics in Healthcare and Government , 2015 .

[94]  Holger Ziekow,et al.  Towards a Big Data Analytics Framework for IoT and Smart City Applications , 2015 .

[95]  Shikha Agrawal,et al.  Neural Network Techniques for Cancer Prediction: A Survey , 2015, KES.

[96]  Taghi M. Khoshgoftaar,et al.  Deep learning applications and challenges in big data analytics , 2015, Journal of Big Data.

[97]  Jian Dong,et al.  Towards Unified Object Detection and Semantic Segmentation , 2014, ECCV.

[98]  K. Marsolo,et al.  Applications of Business Analytics in Healthcare. , 2014, Business horizons.

[99]  Michael J. Crawley,et al.  Analytics in empirical/archival financial accounting research , 2014 .

[100]  Philip S. Yu,et al.  Detecting deception in Online Social Networks , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[101]  C. L. Philip Chen,et al.  Data-intensive applications, challenges, techniques and technologies: A survey on Big Data , 2014, Inf. Sci..

[102]  Trevor Darrell,et al.  LSDA: Large Scale Detection through Adaptation , 2014, NIPS.

[103]  Shonali Krishnaswamy,et al.  Mobile Big Data Analytics: Research, Practice, and Opportunities , 2014, 2014 IEEE 15th International Conference on Mobile Data Management.

[104]  N. Kshetri.  The emerging role of Big Data in key development issues: Opportunities, challenges, and concerns , 2014, Big Data Soc..

[105]  Vipin Kumar,et al.  Trends in big data analytics , 2014, J. Parallel Distributed Comput..

[106]  Alexandros Nanopoulos,et al.  Storage-optimizing clustering algorithms for high-dimensional tick data , 2014, Expert Syst. Appl..

[107]  Yonggang Wen,et al.  Toward Scalable Systems for Big Data Analytics: A Technology Tutorial , 2014, IEEE Access.

[108]  Bin Zhao,et al.  Quasi Real-Time Summarization for Consumer Videos , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[109]  Zahir Tari,et al.  A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis , 2014, IEEE Transactions on Emerging Topics in Computing.

[110]  Xiaogang Wang,et al.  Multi-source Deep Learning for Human Pose Estimation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[111]  Leslie P. Willcocks,et al.  Digitisation, ‘Big Data’ and the transformation of accounting information , 2014 .

[112]  Xue-wen Chen,et al.  Big Data Deep Learning: Challenges and Perspectives , 2014, IEEE Access.

[113]  David E. Stout,et al.  Focusing accounting curricula on students' long-run careers: recommendations for an integrated competency-based framework for accounting education , 2014 .

[114]  Shan Suthaharan,et al.  Big data classification: problems and challenges in network intrusion prediction with machine learning , 2014, PERV.

[115]  Wingyan Chung,et al.  BizPro: Extracting and categorizing business intelligence factors from textual news articles , 2014, Int. J. Inf. Manag..

[116]  Yunhao Liu,et al.  Big Data: A Survey , 2014, Mob. Networks Appl..

[117]  Alejandro Peña-Ayala.  Review: Educational data mining: A survey and a data mining-based analysis of recent works , 2014 .

[118]  Phil Simon,et al.  The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions , 2014 .

[119]  Viju Raghupathi,et al.  Big data analytics in healthcare: promise and potential , 2014, Health Information Science and Systems.

[120]  Kurt Fanning,et al.  Big Data: New Opportunities for M&A , 2014 .

[121]  Jianping Li,et al.  Framework Formation of Financial Data Classification Standard in the Era of the Big Data , 2014 .

[122]  J. Lee,et al.  Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial Informatics , 2014 .

[123]  Han Zhao,et al.  Extreme learning machine: algorithm, theory and applications , 2013, Artificial Intelligence Review.

[124]  Muhammad Atif Tahir,et al.  Towards cloud based big data analytics for smart future cities , 2013, 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing.

[125]  Hyun Yoe,et al.  Agricultural Production System Based on IoT , 2013, 2013 IEEE 16th International Conference on Computational Science and Engineering.

[126]  Davide Taibi,et al.  A semantic approach to mobile learning analytics , 2013, TEEM '13.

[127]  Marc J. Schniederjans,et al.  Enhancing financial performance with social media: An impression management perspective , 2013, Decis. Support Syst..

[128]  Amit P. Sheth,et al.  From Data to Actionable Knowledge: Big Data Challenges in the Web of Things , 2013, IEEE Intell. Syst..

[129]  Nada Lavrac,et al.  Semantic Data Mining of Financial News Articles , 2013, Discovery Science.

[130]  Cong Wang,et al.  Applications and Implementation of Decomposition Storage Model (DSM) in Paas of Agricultural , 2013, CCTA.

[131]  Haluk Demirkan,et al.  A Smart Healthcare Systems Framework , 2013, IT Professional.

[132]  Uma Srinivasan,et al.  Leveraging Big Data Analytics to Reduce Healthcare Costs , 2013, IT Professional.

[133]  Jelena Fiosina,et al.  Big Data Processing and Mining for Next Generation Intelligent Transportation Systems , 2013 .

[134]  Amaury Lendasse,et al.  Fast Face Recognition Via Sparse Coding and Extreme Learning Machine , 2013, Cognitive Computation.

[135]  Albert Y. Zomaya,et al.  A Bee Colony based optimization approach for simultaneous job scheduling and data replication in grid environments , 2013, Comput. Oper. Res..

[136]  S. Fawcett,et al.  Data Science, Predictive Analytics, and Big Data: A Revolution that Will Transform Supply Chain Design and Management , 2013 .

[137]  Zhu-Hong You,et al.  Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis , 2013, BMC Bioinformatics.

[138]  Yoshua Bengio,et al.  Deep Learning of Representations: Looking Forward , 2013, SLSP.

[139]  Charbel José Chiappetta Jabbour,et al.  Environmental training in organisations: From a literature review to a framework for future research , 2013 .

[140]  Xiaoyong Du,et al.  Big data challenge: a data management perspective , 2013, Frontiers of Computer Science.

[141]  B. Schrauwen,et al.  Reservoir computing and extreme learning machines for non-linear time-series data analysis , 2013, Neural Networks.

[142]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[143]  Wei Chen,et al.  Influence diffusion dynamics and influence maximization in social networks with friend and foe relationships , 2011, WSDM.

[144]  Neal Leavitt.  Bringing big analytics to the masses , 2013, Computer.

[145]  Wolfgang Lehner,et al.  The Graph Story of the SAP HANA Database , 2013, BTW.

[146]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[147]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[148]  Wilfred Ng,et al.  A model-based approach for RFID data stream cleansing , 2012, CIKM.

[149]  Seref Sagiroglu,et al.  Data mining and wind power prediction: A literature review , 2012 .

[150]  Chen Li,et al.  Big data platforms: What's next? , 2012, XRDS.

[151]  Shu-Hsien Liao,et al.  Data mining techniques and applications - A decade review from 2000 to 2011 , 2012, Expert Syst. Appl..

[152]  Bir Bhanu,et al.  Image super-resolution by extreme learning machine , 2012, 2012 19th IEEE International Conference on Image Processing.

[153]  Ian Piper,et al.  A linked data approach to assessing medical data , 2012, 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS).

[154]  Christie I. Ezeife,et al.  Data mining techniques for design of ITS student models , 2012, EDM.

[155]  Seunghak Lee,et al.  Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs , 2012, Bioinform..

[156]  George O. Strawn.  Scientific Research: How Many Paradigms?. , 2012 .

[157]  Imad Aad,et al.  The Mobile Data Challenge: Big Data for Mobile Computing Research , 2012 .

[158]  Paul Zikopoulos,et al.  Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data , 2011 .

[159]  Carole A. Goble,et al.  Quality, trust, and utility of scientific data on the web: towards a joint model , 2011, WebSci '11.

[160]  Dianhui Wang,et al.  Extreme learning machines: a survey , 2011, Int. J. Mach. Learn. Cybern..

[161]  Paras Mandal,et al.  A review of wind power and wind speed forecasting methods with different time horizons , 2010, North American Power Symposium 2010.

[162]  Henry C. Lucas,et al.  What is Your Digital Business Strategy? , 2010, IT Prof..

[163]  Eric Séverin,et al.  OPELM and OPKNN in long-term prediction of time series using projected input data , 2010, Neurocomputing.

[164]  Padmini Srinivasan,et al.  On the predictive ability of narrative disclosures in annual reports , 2010, Eur. J. Oper. Res..

[165]  Bernardo A. Huberman,et al.  Predicting the Future with Social Media , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[166]  Zhi-Zhong Mao,et al.  An Ensemble ELM Based on Modified AdaBoost.RT Algorithm for Predicting the Temperature of Molten Steel in Ladle Furnace , 2010, IEEE Transactions on Automation Science and Engineering.

[167]  Julia Hirschberg,et al.  “You’re as Sick as You Sound”: Using Computational Approaches for Modeling Speaker State to Gauge Illness and Recovery , 2010 .

[168]  Engelbert Mephu Nguifo,et al.  Protein sequences classification by means of feature extraction with substitution matrices , 2010, BMC Bioinformatics.

[169]  Qing He,et al.  Parallel K-Means Clustering Based on MapReduce , 2009, CloudCom.

[170]  Ryan S. Baker,et al.  The State of Educational Data Mining in 2009: A Review and Future Visions. , 2009, EDM 2009.

[171]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[172]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[173]  Li Xiu,et al.  Application of data mining techniques in customer relationship management: A literature review and classification , 2009, Expert Syst. Appl..

[174]  A. Pentland,et al.  Life in the network: The coming age of computational social science: Science , 2009 .

[175]  Edoardo M. Airoldi,et al.  Mixed Membership Stochastic Blockmodels , 2007, NIPS.

[176]  Sanjay Ghemawat,et al.  MapReduce: simplified data processing on large clusters , 2008, CACM.

[177]  R. Wiener.  Editorial , 1903, J. Object Technol..

[178]  Sajal K. Das,et al.  A Middleware Framework for Ambiguous Context Mediation in Smart Healthcare Application , 2007, Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007).

[179]  Pearl Brereton,et al.  Lessons from applying the systematic literature review process within the software engineering domain , 2007, J. Syst. Softw..

[180]  Carlos Castillo,et al.  Effective web crawling , 2005, SIGF.

[181]  Bruce G. Buchanan,et al.  Ontology-guided knowledge discovery in databases , 2001, K-CAP '01.

[182]  Guoqiang Peter Zhang,et al.  Neural networks for classification: a survey , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[183]  D. Himmelblau.  Applications of artificial neural networks in chemical engineering , 2000 .

[184]  Lluís Màrquez Villodre.  Machine learning and natural language processing , 2000 .

[185]  Lluis Marquez,et al.  Machine Learning and Natural Language Processing , 2000 .

[186]  Tasadduq A. Shervani,et al.  Market-Based Assets and Shareholder Value: A Framework for Analysis , 1998 .

[187]  M. Cox,et al.  Application-controlled demand paging for out-of-core visualization , 1997, Proceedings. Visualization '97 (Cat. No. 97CB36155).

[188]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery in Databases , 1996, AI Mag..

[189]  D. Sankoff,et al.  RNA secondary structures and their prediction , 1984 .

[190]  P. Kotler,et al.  Principles of Marketing , 1983 .

[191]  Jaime G. Carbonell,et al.  A tutorial on techniques and applications for natural language processing , 1983 .