Data mining

This book introduces readers to advanced data science techniques for signal mining in connection with agriculture.

This book constitutes the thoroughly refereed proceedings of the 35th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2022, held in Kitakyushu, Japan, in July 2022.

This book constitutes the refereed proceedings of the 15th IAPR International Workshop on Document Analysis Systems, DAS 2022, held in La Rochelle, France, in May 2022.

This book constitutes the proceedings of the 7th International Conference on Business Intelligence, CBI 2022, which took place in Khouribga, Morocco, during May 26-28, 2022.

In this book, we primarily focus on studies that provide objective, unobtrusive, and innovative measures (e.

This book constitutes the refereed proceedings of the 4th International Conference on Adaptive Instructional Systems, AIS 2022, held as part of the 23rd International Conference, HCI International 2022, which was held virtually in June/July 2022.

This book constitutes the refereed proceedings of the Third International Conference on Soft Computing and its Engineering Applications, icSoftComp 2021, held in Changa, India, in December 2021.

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing.

This book constitutes the refereed proceedings of the 5th International Conference on Emerging Technologies in Computer Engineering, ICETCE 2021, held in Jaipur, India, in February 2022.

The 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China.

This book constitutes revised selected papers from the 27th Argentine Congress on Computer Science, CACIC 2021, held in Salta, Argentina in October 2021.

This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world.

This book constitutes the refereed proceedings of the 13th International ICT Innovations Conference, ICT Innovations 2021, held as virtual event in September 2021.

This book collects ground-breaking works on the actual and potential impact of big data and data-integrated design for resilient urban environments, including human- and ecology-centred perspectives.

When you picture human-data interactions (HDI), what comes to mind?

This book focusses on techniques for automating the procedure of creating external labelings, also known as callout labelings.

The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges.

There is ample evidence in the visualization community that individual differences matter.

At the 2016 IEEE VIS Conference in Baltimore, Maryland, a panel of experts from the Scientific Visualization (SciVis) community gathered to discuss why the SciVis component of the conference had been shrinking significantly for over a decade.

Prevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data.

This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation.

Visualization has become a valuable means for data exploration and analysis.

Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making.

Displaying multiple levels of data visually has been proposed to address the challenge of limited screen space.

Visual analytics has come a long way since its inception in 2005.

Interest in visualization design has increased in recent years.

Our society has entered a data-driven era, one in which not only are enormous amounts of data being generated daily but there are also growing expectations placed on the analysis of this data.

This book constitutes the refereed proceedings of the 9th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2019, held in Poznan, Poland, in May 2019.

Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses.

In the past decade, social media has become increasingly popular for news consumption due to its easy access, fast dissemination, and low cost.

Unstructured text, as one of the most important data forms, plays a crucial role in data-driven decision making in domains ranging from social networking and information retrieval to scientific research and healthcare informatics.

This book presents pattern-based problem-solving methods for a variety of machine learning and data analysis problems.

The real-world data, though massive, is largely unstructured, in the form of natural-language text.

Graphs naturally represent information ranging from links between web pages, to communication in email networks, to connections between neurons in our brains.

A lot of digital ink has been spilled on "e;big data"e; over the past few years.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments.

In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook Places, which have attracted an increasing number of users and greatly enriched their urban experience.

The "e;big data"e; era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life.

Social media shatters the barrier to communicate anytime anywhere for people of all walks of life.

What does the Web look like?

Real-world physical and abstract data objects are interconnected, forming gigantic, interconnected networks.

This synthesis lecture provides a survey of work on privacy in online social networks (OSNs).

The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways.

This book offers a comprehensive overview of the various concepts and research issues about blogs or weblogs.

The importance of accurate recommender systems has been widely recognized by academia and industry, and recommendation is rapidly becoming one of the most successful applications of data mining and machine learning.

Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc.

Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade.

These days, nearly all the engineering problem are solved with the aid of suitable computer packages.

Feedback control systems is an important course in aerospace engineering, chemical engineering, electrical engineering, mechanical engineering, and mechatronics engineering, to name just a few.

This lecture provides an introduction to the field of mobile robotics and the intersection between multiple robotics-related disciplines including electrical, mechanical, computer, software engineering and computer science.