This book constitutes the refereed proceedings of the 27th China Conference on Information Retrieval, CCIR 2021, held in Dalian, China, in October 2021.
At a fundamental level, service-oriented crowdsourcing applies the principles of service-oriented architecture (SOA) to the discovery, composition and selection of a scalable human workforce.
Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down.
A poorly performing database application not only costs users time, but also has an impact on other applications running on the same computer or the same network.
Get hands-on with deploying and managing your database services to provide scalable and high-speed data access on CockroachDBKey FeaturesGain insights into CockroachDB and build highly reliable cloud-native applicationsExplore the power of a scalable and highly available cloud-native SQL database to distribute data and workloads automaticallyBuild high-speed database services using CockroachDB and troubleshoot performance issuesBook DescriptionGetting Started with CockroachDB will introduce you to the inner workings of CockroachDB and help you to understand how it provides faster access to distributed data through a SQL interface.
This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs.
This book constitutes the refereed proceedings of the 32nd Canadian Conference on Artificial Intelligence, Canadian AI 2019, held in Kingston, ON, Canada, in May 2019.
This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment.
Interdisciplinary approaches using Machine Learning and Deep Learning techniques are smartly addressing real life challenges and have emerged as an inseparable element of disruption in current times.
This volume presents the latest advances in statistics and data science, including theoretical, methodological and computational developments and practical applications related to classification and clustering, data gathering, exploratory and multivariate data analysis, statistical modeling, and knowledge discovery and seeking.
This book constitutes revised papers from the five workshops which were held during June 2020 at the 23rd International Conference on Business Information Systems, BIS 2020.
"e;Ulf Mattsson leverages his decades of experience as a CTO and security expert to show how companies can achieve data compliance without sacrificing operability.
Provides a foundation in classical parametric methods of regression and classification essential for pursuing advanced topics in predictive analytics and statistical learning This book covers a broad range of topics in parametric regression and classification including multiple regression, logistic regression (binary and multinomial), discriminant analysis, Bayesian classification, generalized linear models and Cox regression for survival data.
This book focuses on Entity Discovery and Linking (EDL), which is the problem of identifying concepts and entities, disambiguating them, and grounding them to one or more knowledge bases (KBs).
This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy.
This book constitutes the refereed proceedings of the 12th International Conference on Similarity Search and Applications, SISAP 2019, held in Newark, NJ, USA, in October 2019.
This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data.
Acquire and analyze data from all corners of the social web with PythonAbout This BookMake sense of highly unstructured social media data with the help of the insightful use cases provided in this guideUse this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social dataThis is your one-stop solution to fetching, storing, analyzing, and visualizing social media dataWho This Book Is ForThis book is for intermediate Python developers who want to engage with the use of public APIs to collect data from social media platforms and perform statistical analysis in order to produce useful insights from data.
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021.
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020.
This two-volume set LNCS 11625 and 11626 constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Education, AIED 2019, held in Chicago, IL, USA, in June 2019.
This book provides a thorough exploration of the intersection between gender-based healthcare disparities and the transformative potential of artificial intelligence (AI) and machine learning (ML).
This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2020, which took place during December 15-18, 2020, in Sonepat, India.
This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.
This text integrates different mobility data handling processes, from database management to multi-dimensional analysis and mining, into a unified presentation driven by the spectrum of requirements raised by real-world applications.
Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV.
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge.
This book constitutes the refereed proceedings of the 14th International Conference on Scalable Uncertainty Management, SUM 2020, which was held in Bozen-Bolzano, Italy, in September 2020.
Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R.
This updated book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications.
With the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data.
Although there are already some books published on Big Data, most of them only cover basic concepts and society impacts and ignore the internal implementation details-making them unsuitable to R&D people.
Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R.
