Big Data Fusion Model for Heterogeneous Financial Market Data (FinDf)
暂无分享,去创建一个
[1] Marco A. Solano,et al. Enterprise data architecture principles for High-Level Multi-Int fusion: A pragmatic guide for implementing a heterogeneous data exploitation framework , 2012, 2012 15th International Conference on Information Fusion.
[2] Hosagrahar V. Jagadish,et al. Big data challenges and opportunities in financial stability monitoring , 2016 .
[3] Chee,et al. Cashtags and Sentiment Analysis in Predicting Stock Price Movements , 2017 .
[4] Lucien Wald,et al. Data fusion : a conceptual approach for an efficient exploitation of remote sensing images , 1998 .
[5] Miriam A. M. Capretz,et al. Challenges for MapReduce in Big Data , 2014, 2014 IEEE World Congress on Services.
[6] Osmar R. Zaïane,et al. Data Mining Applications for Fraud Detection in Securities Market , 2012, 2012 European Intelligence and Security Informatics Conference.
[7] P. Manning. Financial journalism, news sources and the banking crisis , 2013 .
[8] Wei Wei,et al. Twitter volume spikes and stock options pricing , 2016, Comput. Commun..
[9] Shahriar Akter,et al. Big data analytics in electronic markets , 2017, Electron. Mark..
[10] Jesús García,et al. Context-based Information Fusion: A survey and discussion , 2015, Inf. Fusion.
[11] Fakhri Karray,et al. Multisensor data fusion: A review of the state-of-the-art , 2013, Inf. Fusion.
[12] Vijay Borges,et al. Survey of context information fusion for ubiquitous Internet-of-Things (IoT) systems , 2016, Open Comput. Sci..
[13] Wolfgang Jank,et al. Real-Time Diffusion of Information on Twitter and the Financial Markets , 2016, PloS one.
[14] W. Currie,et al. A model for unpacking big data analytics in high-frequency trading , 2017 .
[15] James M. Conrad,et al. A survey of multisensor fusion techniques, architectures and methodologies , 2017, SoutheastCon 2017.
[16] Michele Zappavigna,et al. Discourse of Twitter and social media , 2012 .
[17] Maamoun Ahmed,et al. Data Mining and Fusion Techniques for WSNs as a Source of the Big Data , 2015 .
[18] Erik Blasch,et al. Revisiting the JDL model for information exploitation , 2013, Proceedings of the 16th International Conference on Information Fusion.
[19] C. L. Philip Chen,et al. Data-intensive applications, challenges, techniques and technologies: A survey on Big Data , 2014, Inf. Sci..
[20] Clare Stanier,et al. Defining Big Data , 2016, BDAW '16.
[21] Fabrizio Lillo,et al. A Large Scale Study to Understand the Relation between Twitter and Financial Market , 2016, 2016 Third European Network Intelligence Conference (ENIC).
[22] Werner Antweiler,et al. Is All that Talk Just Noise? The Information Content of Internet Stock Message Boards , 2001 .
[23] Magdy Bayoumi,et al. Data Fusion in WSN , 2012 .
[24] M. Bevilacqua,et al. Data Fusion Strategy for Precise Vehicle Location for Intelligent Self-Aware Maintenance Systems , 2015, 2015 6th International Conference on Intelligent Systems, Modelling and Simulation.
[25] Rasmus Bro,et al. Understanding data fusion within the framework of coupled matrix and tensor factorizations , 2013 .
[26] H. Chen. Group polarization in virtual communities: The case of stock message boards , 2013 .
[27] Frank C. Graves,et al. Computerized and High‐Frequency Trading , 2014 .
[28] Keeley A. Crockett,et al. Experiment for Analysing the Impact of Financial Events on Twitter , 2017, ICA3PP.
[29] Stefan Stieglitz,et al. #IronyOff - Understanding the Usage of Irony on Twitter during a Corporate Crisis , 2017, PACIS.
[30] James Llinas,et al. Revisiting the JDL Data Fusion Model II , 2004 .
[31] Rachelle Vessey. Zappavigna, M. (2012). Discourse of Twitter and Social Media: How We Use Language to Create Affiliation on the Web. London: Bloomsbury , 2015 .
[32] Christoffer Hallstensen,et al. Multisensor Fusion for Intrusion Detection and Situational Awareness , 2017 .
[33] Aaron Elliot,et al. Time Series Prediction : Predicting Stock Price , 2017 .
[34] Seref Sagiroglu,et al. Big data: A review , 2013, 2013 International Conference on Collaboration Technologies and Systems (CTS).
[35] Elena Console,et al. Data Fusion , 2009, Encyclopedia of Database Systems.
[36] L. Harris. Trading and Exchanges: Market Microstructure for Practitioners , 2002 .
[37] Christian Schindelhauer,et al. Data Fusion of Time Stamps and Transmitted Data for Unsynchronized Beacons , 2015, IEEE Sensors Journal.
[38] Lars Christian Andersen,et al. Data-driven Approach to Information Sharing using Data Fusion and Machine Learning , 2016 .
[39] GeunSik Jo,et al. Smart Data: Where the Big Data Meets the Semantics , 2017, Comput. Intell. Neurosci..
[40] Mathias Ekstedt,et al. Automated architecture modeling for enterprise technology manageme using principles from data fusion: A security analysis case , 2016, 2016 Portland International Conference on Management of Engineering and Technology (PICMET).
[41] Serge Chaumette,et al. Using heterogeneous multilevel swarms of UAVs and high-level data fusion to support situation management in surveillance scenarios , 2016, 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).
[42] Xiaomo Liu,et al. funSentiment at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs Using Word Vectors Built from StockTwits and Twitter , 2017, *SEMEVAL.
[43] Daniel H. Boylan. The innovative use of Twitter technology by bank leadership to enhance shareholder value , 2016 .
[44] Tomer Geva,et al. Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news , 2014, Decis. Support Syst..
[45] H. V. Jagadish,et al. Research Challenges in Financial Data Modeling and Analysis , 2017, Big Data.
[46] Osmar R. Zaïane,et al. Time series contextual anomaly detection for detecting market manipulation in stock market , 2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA).
[47] Florin Radulescu,et al. MongoDB vs Oracle -- Database Comparison , 2012, 2012 Third International Conference on Emerging Intelligent Data and Web Technologies.
[48] James H. Garrett,et al. A data fusion approach for track monitoring from multiple in-service trains , 2017 .
[49] Jason J. Jung,et al. Social big data: Recent achievements and new challenges , 2015, Information Fusion.
[50] Francisco Herrera,et al. Big data preprocessing: methods and prospects , 2016 .
[51] Pascal Vasseur,et al. Introduction to Multisensor Data Fusion , 2005, The Industrial Information Technology Handbook.
[52] Songting Chen,et al. Cheetah , 2010, Proc. VLDB Endow..
[53] Caiyun Zhang,et al. Applying data fusion techniques for benthic habitat mapping and monitoring in a coral reef ecosystem , 2015 .
[54] Tomer Geva,et al. Predicting Intraday Stock returns by Integrating Market Data and Financial News Reports , 2010, MCIS.
[55] Ammar Belatreche,et al. Pre-processing online financial text for sentiment classification: A natural language processing approach , 2014, 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).
[56] Rajasekar Krishnamurthy,et al. Extracting, Linking and Integrating Data from Public Sources: A Financial Case Study , 2015, IEEE Data Eng. Bull..
[57] Jitendra R. Raol,et al. Multi-Sensor Data Fusion with MATLAB® , 2009 .
[58] Alan N. Steinberg,et al. Revisions to the JDL data fusion model , 1999, Defense, Security, and Sensing.
[59] Mohammad. M. AlyanNezhadi,et al. An efficient algorithm for multisensory data fusion under uncertainty condition , 2017 .
[60] Keeley A. Crockett,et al. Financial Discussion Boards Irregularities Detection System (FDBs-IDS) using information extraction , 2017, 2017 Intelligent Systems Conference (IntelliSys).
[61] Federico Castanedo,et al. A Review of Data Fusion Techniques , 2013, TheScientificWorldJournal.