Analysis and Prediction of Web User Interactions Using Time Series Analysis
Title | Analysis and Prediction of Web User Interactions Using Time Series Analysis PDF eBook |
Author | Vijay Vyas Mohan |
Publisher | |
Pages | |
Release | 2009 |
Genre | |
ISBN |
Understanding User-Web Interactions Via Web Analytics
Title | Understanding User-Web Interactions Via Web Analytics PDF eBook |
Author | Bernard J. Jansen |
Publisher | Morgan & Claypool Publishers |
Pages | 117 |
Release | 2009 |
Genre | Computers |
ISBN | 1598298518 |
This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of user-Website interactions. Table of Contents: Understanding Web Analytics / The Foundations of Web Analytics: Theory and Methods / The History of Web Analytics / Data Collection for Web Analytics / Web Analytics Fundamentals / Web Analytics Strategy / Web Analytics as Competitive Intelligence / Supplementary Methods for Augmenting Web Analytics / Search Log Analytics / Conclusion / Key Terms / Blogs for Further Reading / References
Time Series Analysis
Title | Time Series Analysis PDF eBook |
Author | Chun-Kit Ngan |
Publisher | BoD – Books on Demand |
Pages | 131 |
Release | 2019-11-06 |
Genre | Mathematics |
ISBN | 1789847788 |
This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This book is divided into three sections and each section includes two chapters. Section 1 discusses analyzing multivariate and fuzzy time series. Section 2 focuses on developing deep neural networks for time series forecasting and classification. Section 3 describes solving real-world domain-specific problems using time series techniques. The concepts and techniques contained in this book cover topics in time series research that will be of interest to students, researchers, practitioners, and professors in time series forecasting and classification, data analytics, machine learning, deep learning, and artificial intelligence.
Practical Time Series Analysis
Title | Practical Time Series Analysis PDF eBook |
Author | Aileen Nielsen |
Publisher | O'Reilly Media |
Pages | 500 |
Release | 2019-09-20 |
Genre | Computers |
ISBN | 1492041629 |
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
Time Series Prediction
Title | Time Series Prediction PDF eBook |
Author | Andreas S. Weigend |
Publisher | Routledge |
Pages | 663 |
Release | 2018-05-04 |
Genre | Social Science |
ISBN | 0429961197 |
The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques that are used to study time series, both as a reference for experts and as a guide for novices.
Time Series Analysis, Modeling and Applications
Title | Time Series Analysis, Modeling and Applications PDF eBook |
Author | Witold Pedrycz |
Publisher | Springer |
Pages | 404 |
Release | 2012-11-26 |
Genre | Computers |
ISBN | 9783642334405 |
Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological and algorithmic approaches and case studies. This volume is aimed at a broad audience of researchers and practitioners engaged in various branches of operations research, management, social sciences, engineering, and economics. Owing to the nature of the material being covered and a way it has been arranged, it establishes a comprehensive and timely picture of the ongoing pursuits in the area and fosters further developments.
An Analysis of User Behavior on the Web
Title | An Analysis of User Behavior on the Web PDF eBook |
Author | Eelco Herder |
Publisher | VDM Publishing |
Pages | 240 |
Release | 2007 |
Genre | Computers |
ISBN | 9783836428187 |
At first sight, browsing the World Wide Web is a fairly intuitive and simple activity, but it turns out that users often experience difficulties in finding the information and services that they are looking for - or in returning to items that they have visited before. In order to improve the current design of Web sites and Web browsers, or to provide users with personalized interfaces, one needs to know how users interact with the Web. Although theoretical models and empirical data exist, the knowledge that they provide is limited and scattered. In this book, we integrate current insights and extend this body of knowledge with a number of user studies. Several methods are presented for obtaining, clearing, analyzing and visualizing Web usage data. Various aspects of user navigation styles are discussed. Particular attention is given to the issue why, when and how often users return to Web pages, and how browsers can support this more effectively. An important observation is that the Web has evolved from a hypermedia system to a hybrid between hypermedia and interactive applications. This book targets researchers and professionals who want to better understand and support the users that visit their Web sites or that make use of their applications and tools.