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Minimalism
by Hartmut ObendorfThe notion of Minimalism is proposed as a theoretical tool supporting a more differentiated understanding of reduction and thus forms a standpoint that allows definition of aspects of simplicity. Possible uses of the notion of minimalism in the field of human-computer interaction design are examined both from a theoretical and empirical viewpoint, giving a range of results. Minimalism defines a radical and potentially useful perspective for design analysis. The empirical examples show that it has also proven to be a useful tool for generating and modifying concrete design techniques. Divided into four parts this book traces the development of minimalism, defines the four types of minimalism in interaction design, looks at how to apply it and finishes with some conclusions.
The Minimalist Entrepreneur: How Great Founders Do More with Less
by Sahil Lavingia&“Pay attention.&”—Jason Fried A revolutionary roadmap for building startups that go the distance Now more than ever, you don&’t need a fancy office, Ivy League degree, or millions of dollars in venture capital to launch a business that matters for the communities you care most about. Software, the internet, and remote work have made it possible for entrepreneurs to start for free, make a customer of anyone, and grow a profitable, sustainable company from anywhere. Packed with hard-won, battle-tested lessons from Lavingia&’s own journey of building Gumroad, a platform for creators to sell their work, The Minimalist Entrepreneur teaches founders how to: • start then learn • build a community, then solve a problem for them • charge for something even before you&’ve built anything • avoid running out of money and, more importantly, energy • run a tight ship amid the rise of the gig economy and remote work • own a business without it owning you back. The Minimalist Entrepreneur is the manifesto for a new generation of founders who would rather build great companies than big ones. This is essential knowledge for every founder aspiring to build a business worth building.
The Minimalist Photographer
by Steve JohnsonThis book covers photography from a minimalist perspective, proving that it is possible to take very good photographs with relatively cheap equipment. The minimalist process emphasizes the importance of first knowing what you want to achieve as a photographer and then choosing the most effective equipment, subject matter, and general approach to meet your goals. The minimalist photographer works with the idea that the brain and the eye are far more important than the camera. Author Steve Johnson begins by asking you, the reader, to look inward and make the connections between your nature and your photography. Why do you want to take photographs and what subject matter are you attracted to? What type of photographer are you now and what type of photographer would you like to become? These are important questions to consider when deciding what approach works best for you. In subsequent chapters, you'll learn about the equipment and workflow of a minimalist photographer as Johnson discusses the strengths and weaknesses of various types of cameras and explains why the biggest or most expensive piece of equipment is not always the best. He also addresses the importance of lighting and teaches you how to achieve effective lighting without spending a lot of money. Also included are discussions about aesthetics and composition, as well as a brief history of photography and the future of the art form.
The Minimum Core for Information and Communication Technology: Audit And Test (Achieving QTLS Series)
by Alan ClarkeThe new UK teacher training framework, introduced in September 2007, requires all teachers in the post-16 sector to possess knowledge, understanding, and personal skills to at least level 2 in the minimum core for information and communication technology (ICT). Coverage and assessment of the minimum core has to be embedded in all UK Certificate and Diploma courses leading to Qualified Teacher Learning and Skills and Associate Teacher Learning and Skills status. This book is a practical guide to ICT for trainee teachers in the lifelong learning sector. It enables trainee teachers to identify and develop their own ICT skills and to support their students in ICT.
The Minimum Core for Information and Communication Technology: Audit And Test (Achieving QTLS Series)
by Sandra MurrayThis book supports trainee teachers in the Lifelong Learning Sector in the assessment of their knowledge of ICT. A self-audit section is included to help trainees understand their level of competence and confidence and will help them identify any gaps in their knowledge and skills. This is followed by exercises and activities to support and enhance learning. The book covers all the content of the LLUK standards for the minimum core for information and communication technology. Coverage and assessment of the core have to be embedded in all Certificate and Diploma courses leading to QTLS and ATLS status.
Mining Complex Networks
by Bogumil Kaminski Pawel Prałat Francois ThebergeThis book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision-making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks aim to understand the principles governing the organization and the behavior of such networks is crucial for a broad range of fields of study. Here are a few selected typical applications of mining networks: Community detection (which users on some social media platforms are close friends). Link prediction (who is likely to connect to whom on such platforms). Node attribute prediction (what advertisement should be shown to a given user of a particular platform to match their interests). Influential node detection (which social media users would be the best ambassadors of a specific product). This textbook is suitable for an upper-year undergraduate course or a graduate course in programs such as data science, mathematics, computer science, business, engineering, physics, statistics, and social science. This book can be successfully used by all enthusiasts of data science at various levels of sophistication to expand their knowledge or consider changing their career path. Jupiter notebooks (in Python and Julia) accompany the book and can be accessed on https://www.ryerson.ca/mining-complex-networks/. These not only contain all the experiments presented in the book, but also include additional material. Bogumił Kamiński is the Chairman of the Scientific Council for the Discipline of Economics and Finance at SGH Warsaw School of Economics. He is also an Adjunct Professor at the Data Science Laboratory at Ryerson University. Bogumił is an expert in applications of mathematical modeling to solving complex real-life problems. He is also a substantial open-source contributor to the development of the Julia language and its package ecosystem. Paweł Prałat is a Professor of Mathematics in Ryerson University, whose main research interests are in random graph theory, especially in modeling and mining complex networks. He is the Director of Fields-CQAM Lab on Computational Methods in Industrial Mathematics in The Fields Institute for Research in Mathematical Sciences and has pursued collaborations with various industry partners as well as the Government of Canada. He has written over 170 papers and three books with 130 plus collaborators. François Théberge holds a B.Sc. degree in applied mathematics from the University of Ottawa, a M.Sc. in telecommunications from INRS and a PhD in electrical engineering from McGill University. He has been employed by the Government of Canada since 1996 where he was involved in the creation of the data science team as well as the research group now known as the Tutte Institute for Mathematics and Computing. He also holds an adjunct professorial position in the Department of Mathematics and Statistics at the University of Ottawa. His current interests include relational-data mining and deep learning.
Mining Data for Financial Applications: 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers (Lecture Notes in Computer Science #11985)
by Valerio Bitetta Ilaria Bordino Andrea Ferretti Francesco Gullo Stefano Pascolutti Giovanni PontiThis book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held in conjunction with ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.
Mining Data for Financial Applications: 5th ECML PKDD Workshop, MIDAS 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers (Lecture Notes in Computer Science #12591)
by Valerio Bitetta Ilaria Bordino Andrea Ferretti Francesco Gullo Giovanni Ponti Lorenzo SeveriniThis 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.*The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain. *The workshop was held virtually due to the COVID-19 pandemic. “Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets” and “Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Mining Intelligence and Knowledge Exploration: 5th International Conference, MIKE 2017, Hyderabad, India, December 13–15, 2017, Proceedings (Lecture Notes in Computer Science #10682)
by Ashish Ghosh, Rajarshi Pal and Rajendra PrasathThis book constitutes the refereed post-conference proceedings of the 5th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2017, held in Hyderabad, India, in December 2017. The 40 full papers presented were carefully reviewed and selected from 139 submissions. The papers were grouped into various subtopics including arti ficial intelligence, machine learning, image processing, pattern recognition, speech processing, information retrieval, natural language processing, social network analysis, security, and fuzzy rough sets.
Mining Intelligence and Knowledge Exploration: 9th International Conference, MIKE 2021, Hammamet, Tunisia, November 1–3, 2021, Proceedings (Lecture Notes in Computer Science #13119)
by Richard Chbeir Yannis Manolopoulos Rajendra PrasathThis book constitutes revised selected papers from the refereed proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2021, which took place in Hammamet, Tunisia, in November 2021. The 22 full papers included in this book were carefully reviewed and selected from 61 submissions. They deal with topics such as evolutionary computation, knowledge exploration in IoT, artificial intelligence, machine learning, data mining and information retrieval, medical image analysis, pattern recognition and computer vision, speech / signal processing, text mining and natural language processing, intelligent security systems, Smart and Intelligent Systems, etc.
Mining Intelligence and Knowledge Exploration: Third International Conference, Mike 2015, Hyderabad, India, December 9-11, 2015, Proceedings (Lecture Notes in Computer Science #9468)
by Adrian Groza Rajendra PrasathThis book constitutes the refereed conference proceedings of the 6th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2018, held in Cluj-Napoca, Romania, in December 2018. The 33 full papers presented were carefully reviewed and selected from 93 submissions. The papers were grouped into various subtopics including evolutionary computation, knowledge exploration in IoT, artificial intelligence, machine learning, image processing, pattern recognition, speech processing, information retrieval, natural language processing, social network analysis, security, and fuzzy rough sets.
Mining Intelligence and Knowledge Exploration: 9th International Conference, MIKE 2023, Kristiansand, Norway, June 28–30, 2023, Proceedings (Lecture Notes in Computer Science #13924)
by Seifedine Kadry Rajendra PrasathThis book constitutes the refereed post-conference proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2023, held in Kristiansand, Norway, during June 28–30, 2023. The 22 full papers and 16 short papers included in this book were carefully reviewed and selected from 87 submissions. They were grouped into various subtopics including Knowledge Exploration in IoT, Medical Informatics, Machine Learning, Text Mining, Natural Language Processing, Cryptocurrency and Blockchain, Application of Artificial Intelligence, and other areas.
Mining Intelligence and Knowledge Exploration
by Rajendra Prasath Alexander GelbukhThis book constitutes the refereed proceedings of theThird International Conference on Mining Intelligence and KnowledgeExploration, MIKE 2015, held in Hyderabad, India, in December 2015. The 48 full papers and 8 short papers presented togetherwith 4 doctoral consortium papers were carefully reviewed and selected from 185submissions. The papers cover a wide range of topics including informationretrieval, machine learning, pattern recognition, knowledge discovery,classification, clustering, image processing, network security, speechprocessing, natural language processing, language, cognition and computation,fuzzy sets, and business intelligence.
Mining Intelligence and Knowledge Exploration
by Rajendra Prasath Anil Kumar Vuppala T. KathirvalavakumarThis book constitutes the refereed proceedings of theThird International Conference on Mining Intelligence and KnowledgeExploration, MIKE 2015, held in Hyderabad, India, in December 2015. The 48 full papers and 8 short papers presented togetherwith 4 doctoral consortium papers were carefully reviewed and selected from 185submissions. The papers cover a wide range of topics including informationretrieval, machine learning, pattern recognition, knowledge discovery,classification, clustering, image processing, network security, speechprocessing, natural language processing, language, cognition and computation,fuzzy sets, and business intelligence.
Mining Intelligence and Knowledge Exploration: 7th International Conference, MIKE 2019, Goa, India, December 19–22, 2019, Proceedings (Lecture Notes in Computer Science #11987)
by Purushothama B. R. Veena Thenkanidiyoor Rajendra Prasath Odelu VangaThis book constitutes the refereed conference proceedings of the 7th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2019, held in Goa, India, in December 2019. The 31 full papers were carefully reviewed and selected from 83 submissions. The accepted papers were chosen on the basis of research excellence, which provides a body of literature for researchers involved in exploring, developing, and validating learning algorithms and knowledge-discovery techniques. Accepted papers were grouped into various subtopics including evolutionary computation, knowledge exploration in IoT, artificial intelligence, machine learning, image processing, pattern recognition, speech processing, information retrieval, natural language processing, social network analysis, security, fuzzy rough sets, and other areas.
Mining Lurkers in Online Social Networks: Principles, Models, and Computational Methods (SpringerBriefs in Computer Science)
by Andrea Tagarelli Roberto InterdonatoThis SpringerBrief brings order to the wealth of research studies that contribute to shape our understanding of on-line social networks (OSNs) lurking phenomena. This brief also drives the development of computational approaches that can be effectively applied to answer questions related to lurking behaviors, as well as to the engagement of lurkers in OSNs. All large-scale online social networks (OSNs) are characterized by a participation inequality principle, i.e., the crowd of an OSN does not actively contribute, rather it takes on a silent role. Silent users are also referred to as lurkers, since they gain benefit from others' information without significantly giving back to the community. Nevertheless, lurkers acquire knowledge from the OSN, therefore a major goal is to encourage them to more actively participate. Lurking behavior analysis has been long studied in social science and human-computer interaction fields, but it has also matured over the last few years in social network analysis and mining. While the main target audience corresponds to computer, network, and web data scientists, this brief might also help increase the visibility of the topic by bridging different closely related research fields. Practitioners, researchers and students interested in social networks, web search, data mining, computational social science and human-computer interaction will also find this brief useful research material .
Mining, Modeling, and Recommending 'Things' in Social Media
by Martin Atzmueller Alvin Chin Christoph Scholz Christoph TrattnerThis book constitutes the thoroughly refereed joint post-workshop proceedings of the 4th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2013, held in Prague, Czech Republic, in September 2013, and the 4th International Workshop on Modeling Social Media, MSM 2013, held in Paris, France, in May 2013. The 8 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. The focus is on collective intelligence in ubiquitous and social environments. Issues tackled include personalization in social streams, recommendations exploiting social and ubiquitous data, and efficient information processing in social systems. Furthermore, this book presents work dealing with the problem of mining patterns from ubiquitous social data, including mobility mining and exploratory methods for ubiquitous data analysis.
Mining Multimedia Documents
by Wahiba Ben Karaa Nilanjan DeyThe information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them. <P><P>Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.
Mining of Massive Datasets
by Jure Leskovec Anand Rajaraman Jeffrey David UllmanThe popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.
Mining of Massive Datasets
by Anand Rajaraman Jeffrey David UllmanThe popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.
Mining Over Air: Wireless Communication Networks Analytics
by Ye Ouyang Mantian Hu Alexis Huet Zhongyuan LiThis book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireless networks domain. Mining Over Air describes the problems and their solutions for wireless network performance and quality, device quality readiness and returns analytics, wireless resource usage profiling, network traffic anomaly detection, intelligence-based self-organizing networks, telecom marketing, social influence, and other important applications in the telecom industry. Written by authors who study big data analytics in wireless networks and telecommunication markets from both industrial and academic perspectives, the book targets the pain points in telecommunication networks and markets through big data. Designed for both practitioners and researchers, the book explores the intersection between the development of new engineering technology and uses data from the industry to understand consumer behavior. It combines engineering savvy with insights about human behavior. Engineers will understand how the data generated from the technology can be used to understand the consumer behavior and social scientists will get a better understanding of the data generation process.
Mining Social Media: Finding Stories in Internet Data
by Lam Thuy VoBuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language.Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media.Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories.Learn how to: • Write Python scripts and use APIs to gather data from the social web • Download data archives and dig through them for insights • Inspect HTML downloaded from websites for useful content • Format, aggregate, sort, and filter your collected data using Google Sheets • Create data visualizations to illustrate your discoveries • Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library • Apply what you've learned to research topics on your ownSocial media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.
Mining Social Networks and Security Informatics
by Zeki Erdem Jon Rokne Suheil Khoury Tansel ÖzyerCrime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for social networks; general aspects of social networks such as pattern and anomaly detection; community discovery; link analysis and spatio-temporal network mining. These topics will be of interest to researchers and practitioners in the general area of security informatics. The volume will also serve as a general reference for readers that would want to become familiar with current research in the fast growing field of cybersecurity.
Mining Software Engineering Data for Software Reuse (Advanced Information and Knowledge Processing)
by Andreas L. Symeonidis Themistoklis DiamantopoulosThis monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance. The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data. Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effort through software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.
Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
by Matthew A. RussellWant to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who's making connections with social media, what they're talking about, and where they're located. You'll learn how to combine social web data, analysis techniques, and visualization to find what you've been looking for in the social haystack--as well as useful information you didn't know existed. Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+ Learn how to employ easy-to-use Python tools to slice and dice the data you collect Explore social connections in microformats with the XHTML Friends Network Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits "A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google