Annals of Data Science最新文献

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Non-negative Sparse Matrix Factorization for Soft Clustering of Territory Risk Analysis 用于领土风险软聚类分析的非负稀疏矩阵因式分解
Annals of Data Science Pub Date : 2024-08-10 DOI: 10.1007/s40745-024-00570-z
Shengkun Xie, Chong Gan, A. Lawniczak
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引用次数: 0
Kernel Method for Estimating Matusita Overlapping Coefficient Using Numerical Approximations 使用数值近似法估算马图西塔重叠系数的核方法
Annals of Data Science Pub Date : 2024-07-27 DOI: 10.1007/s40745-024-00563-y
Omar M. Eidous, Enas A. Ananbeh
{"title":"Kernel Method for Estimating Matusita Overlapping Coefficient Using Numerical Approximations","authors":"Omar M. Eidous, Enas A. Ananbeh","doi":"10.1007/s40745-024-00563-y","DOIUrl":"https://doi.org/10.1007/s40745-024-00563-y","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Maximum Likelihood Estimation for Generalized Inflated Power Series Distributions 广义膨胀幂级数分布的最大似然估计
Annals of Data Science Pub Date : 2024-07-23 DOI: 10.1007/s40745-024-00560-1
Robert L. Paige
{"title":"Maximum Likelihood Estimation for Generalized Inflated Power Series Distributions","authors":"Robert L. Paige","doi":"10.1007/s40745-024-00560-1","DOIUrl":"https://doi.org/10.1007/s40745-024-00560-1","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Farm-Level Smart Crop Recommendation Framework Using Machine Learning 利用机器学习的农场级智能作物推荐框架
Annals of Data Science Pub Date : 2024-07-20 DOI: 10.1007/s40745-024-00534-3
Amit Bhola, Prabhat Kumar
{"title":"Farm-Level Smart Crop Recommendation Framework Using Machine Learning","authors":"Amit Bhola, Prabhat Kumar","doi":"10.1007/s40745-024-00534-3","DOIUrl":"https://doi.org/10.1007/s40745-024-00534-3","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reaction Function for Financial Market Reacting to Events or Information 金融市场对事件或信息的反应函数
Annals of Data Science Pub Date : 2024-07-17 DOI: 10.1007/s40745-024-00565-w
Bo Li, Guangle Du
{"title":"Reaction Function for Financial Market Reacting to Events or Information","authors":"Bo Li,&nbsp;Guangle Du","doi":"10.1007/s40745-024-00565-w","DOIUrl":"10.1007/s40745-024-00565-w","url":null,"abstract":"<div><p>Observations indicate that the distributions of stock returns in financial markets usually do not conform to normal distributions, but rather exhibit characteristics of high peaks, fat tails and biases. In this work, we assume that the effects of events or information on prices obey normal distribution, while financial markets often overreact or underreact to events or information, resulting in non normal distributions of stock returns. Based on the above assumptions, we for the first time propose a reaction function for a financial market reacting to events or information, and a model based on it to describe the distribution of real stock returns. Our analysis of the returns of China Securities Index 300 (CSI 300), the Standard &amp; Poor’s 500 Index (SPX or S &amp;P 500) and the Nikkei 225 Index (N225) at different time scales shows that financial markets often underreact to events or information with minor impacts, overreact to events or information with relatively significant impacts, and react slightly stronger to positive events or information than to negative ones. In addition, differences in financial markets and time scales of returns can also affect the shapes of the reaction functions.</p></div>","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Transmuted Shifted Lindley Distribution: Characterizations, Classical and Bayesian Estimation with Applications 变换的移位林德利分布:特征、经典和贝叶斯估计及其应用
Annals of Data Science Pub Date : 2024-07-16 DOI: 10.1007/s40745-024-00562-z
A. Chakraborty, S. Rana, S. I. Maiti
{"title":"Transmuted Shifted Lindley Distribution: Characterizations, Classical and Bayesian Estimation with Applications","authors":"A. Chakraborty, S. Rana, S. I. Maiti","doi":"10.1007/s40745-024-00562-z","DOIUrl":"https://doi.org/10.1007/s40745-024-00562-z","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141641587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Review of Anonymization Algorithms and Methods in Big Data 大数据中的匿名算法和方法综述
Annals of Data Science Pub Date : 2024-07-13 DOI: 10.1007/s40745-024-00557-w
E. Shamsinejad, T. Banirostam, M. Pedram, A. Rahmani
{"title":"A Review of Anonymization Algorithms and Methods in Big Data","authors":"E. Shamsinejad, T. Banirostam, M. Pedram, A. Rahmani","doi":"10.1007/s40745-024-00557-w","DOIUrl":"https://doi.org/10.1007/s40745-024-00557-w","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141650932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing 使用内存处理来表示大数据流匿名化模型
Annals of Data Science Pub Date : 2024-07-13 DOI: 10.1007/s40745-024-00556-x
E. Shamsinejad, T. Banirostam, M. Pedram, A. Rahmani
{"title":"Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing","authors":"E. Shamsinejad, T. Banirostam, M. Pedram, A. Rahmani","doi":"10.1007/s40745-024-00556-x","DOIUrl":"https://doi.org/10.1007/s40745-024-00556-x","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141651856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analyzing Insurance Data with an Alpha Power Transformed Exponential Poisson Model 用阿尔法幂变换指数泊松模型分析保险数据
Annals of Data Science Pub Date : 2024-07-10 DOI: 10.1007/s40745-024-00554-z
M. Meraou, M. Z. Raqab, Fatmah B. Almathkour
{"title":"Analyzing Insurance Data with an Alpha Power Transformed Exponential Poisson Model","authors":"M. Meraou, M. Z. Raqab, Fatmah B. Almathkour","doi":"10.1007/s40745-024-00554-z","DOIUrl":"https://doi.org/10.1007/s40745-024-00554-z","url":null,"abstract":"","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Unlocking Online Insights: LSTM Exploration and Transfer Learning Prospects 开启在线洞察力:LSTM 探索与迁移学习的前景
Annals of Data Science Pub Date : 2024-07-08 DOI: 10.1007/s40745-024-00551-2
Muhammad Tahir, Sufyan Ali, Ayesha Sohail, Ying Zhang, Xiaohua Jin
{"title":"Unlocking Online Insights: LSTM Exploration and Transfer Learning Prospects","authors":"Muhammad Tahir,&nbsp;Sufyan Ali,&nbsp;Ayesha Sohail,&nbsp;Ying Zhang,&nbsp;Xiaohua Jin","doi":"10.1007/s40745-024-00551-2","DOIUrl":"10.1007/s40745-024-00551-2","url":null,"abstract":"<div><p>Machine learning algorithms can improve the time series data analysis as compared to the traditional methods such as moving averages or auto-regressive approaches. This advancement has helped to unlock several challenging problems since machine learning not only helps to forecast the overall trend of the data, but it also helps to keep the historical track of changes in factors, influencing this trend. These predictions play a pivotal role in almost all areas of research where the observations are time dependent, such as problems ranging from challenges of finance to public health, environmental and climate change challenges. A key challenge of these domains is the higher number of attributes and predictors since managing and manipulating data from many attributes is itself a significant challenge for future forecasting. Addressing these challenges is possible with Recursive Long Short-Term Memory models. The application of such models is crucial, and their efficacy is further amplified when considering transfer learning. During this research, a detailed and comprehensive description of such models is addressed. Practical application is illustrated through an example, emphasizing that these models, when transferred to complex and large datasets using transfer learning, hold great promise.</p></div>","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40745-024-00551-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141667526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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