Hypothesis Based Collaborative Filtering

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Hypothesis Based Collaborative Filtering

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Author : Amancio Bouza
language : en
Publisher: Lulu.com
Release Date : 2012-04-16

Hypothesis Based Collaborative Filtering written by Amancio Bouza and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-16 with Computers categories.

Recommender systems have emerged to help individuals with finding interesting products. As a result, the consumer welfare enhances due to the increased product variety. In other words, recommender systems are essential for increasing consumers welfare, which ultimately leads to an increase of economic and social welfare.Typically, recommender systems use the collective wisdom of individuals for exposing individuals to products which best fits their preferences. More precisely, the most like-minded individuals are considered by the recommender system to provide individuals recommendations. This is commonly referred to as collaborative filtering.In this dissertation, we present hypothesis-based collaborative filtering (HCF) to expose individuals to products which best fits their preferences. HCF retrieves like-minded individuals based on the similarity of their hypothesized preferences by means of machine learning algorithms hypothesizing individuals' preferences.

Influence Of Recommender Systems On Consumer Behavior

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Author : Markus Lill
language : en
Publisher: BoD – Books on Demand
Release Date : 2025-03-13

Influence Of Recommender Systems On Consumer Behavior written by Markus Lill and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Business & Economics categories.

In the dynamic landscape of digital platforms, recommender systems silently guide our decisions, shaping what we watch, read, and buy. But how do these algorithms influence our behavior beyond convenience and personalization? This dissertation delves into the psychological undercurrents of recommender systems, uncovering how subtle design choices trigger behavioral biases that affect consumer preferences, beliefs, and decisions. Through a series of rigorous field experiments, this work explores three critical dimensions of recommender systems: item selection, ranking, and recommendation design. It reveals how phenomena like assimilation and contrast effects, as well as visual cues such as product badges, can subtly yet powerfully steer consumer behavior. Challenging traditional recommender system design priorities, the findings highlight that similarity can sometimes outweigh diversity and that strategic positioning can defy conventional assumptions about user attention. Combining a systematic literature review with empirical evidence from real-world settings, this dissertation offers insights into the interplay between technology and human cognition. It is an essential read for scholars, practitioners, and platform designers seeking to understand - and ethically harness - the behavioral dynamics of recommender systems.

Data Science From Scratch

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Author : Joel Grus
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-04-12

Data Science From Scratch written by Joel Grus and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-12 with Computers categories.

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.

Collaborative Filtering Recommender Systems

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Author : Michael D. Ekstrand
language : en
Publisher: Now Publishers Inc
Release Date : 2011

Collaborative Filtering Recommender Systems written by Michael D. Ekstrand and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.

Collaborative Filtering Recommender Systems discusses a wide variety of the recommender choices available and their implications, providing both practitioners and researchers with an introduction to the important issues underlying recommenders and current best practices for addressing these issues.

Innovative Intelligent Industrial Production And Logistics

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Author : Michele Dassisti
language : en
Publisher: Springer Nature
Release Date : 2025-02-13

Innovative Intelligent Industrial Production And Logistics written by Michele Dassisti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-13 with Computers categories.

This two-volume set CCIS 2372-2373 constitutes the proceedings of the 5th International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2024, held in Porto, Portugal, during November 21–22, 2024. The total of 15 full papers, along with 38 short papers, presented together in this book was carefully reviewed and selected from 76 submissions. This conference focuses on research and development involving innovative methods, software and hardware, whereby intelligent systems are applied to industrial production and logistics. This is currently related to the concept of industry 5.0 - an expression the new wave that extends the trend towards automation and data exchange in manufacturing technologies and processes – including cyber-physical systems, the industrial internet of things, industrial robotics, cloud computing, cognitive computing and artificial intelligence - towards the new role of human resources cooperating with these technologies.

Accelerating Knowledge Sharing Creativity And Innovation Through Business Tourism

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Author : Bari, Muhammad Waseem
language : en
Publisher: IGI Global
Release Date : 2020-04-10

Accelerating Knowledge Sharing Creativity And Innovation Through Business Tourism written by Bari, Muhammad Waseem and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-10 with Business & Economics categories.

Business tourism is a newly coined terminology in social sciences and management literature. It is defined as individuals traveling and staying outside of their hometowns for not more than one successive year for the purpose of enjoyment and other drives (e.g., learning and business activities). Key business tourism activities include attending a variety of meetings, conferences, and workshops as well as exhibitions. Understanding the negative and positive aspects of business tourism is essential to promoting employee learning and knowledge transfer skills. Accelerating Knowledge Sharing, Creativity, and Innovation Through Business Tourism is an essential reference source that discusses how differences in cultures, communities, rituals, norms, and scope of business tourism could influence knowledge sharing practices. Moreover, this book promotes an understanding on how to learn from different cultures and enhance absorptive capacity by interacting with different personalities and cultures. Featuring research on topics such as knowledge management, social capital, and consumer behavior, this book is ideally designed for business professionals, managers, administrators, hotel executives, IT specialists, executives, entrepreneurs, managing directors, and students looking to boost their existing skills and expertise with innovation and creativity by interacting with others and in a new context.

Advances In User Modeling

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Author : Liliana Ardissono
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-24

Advances In User Modeling written by Liliana Ardissono and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-24 with Computers categories.

This book constitutes selected papers from the lectures given at the workshops held in conjunction with the User Modeling, Adaptation and Personalization Conference, UMAP 2011, Girona, Spain, in July 2011. The 40 papers presented were carefully reviewed and selected for inclusion in this book. For each workshop there is an overview paper summarizing the workshop themes, the accepted contributions and the future research trends. In addition the volume presents a selection of the best poster papers of UMAP 2011. The workshops included are: AST, adaptive support for team collaboration; AUM, augmenting user models with real worlds experiences to enhance personalization and adaptation; DEMRA, decision making and recommendation acceptance issues in recommender systems; PALE, personalization approaches in learning environments; SASWeb, semantic adaptive social web; TRUM, trust, reputation and user modeling; UMADR, user modeling and adaptation for daily routines: providing assistance to people with special and specific needs; UMMS, user models for motivational systems: the affective and the rational routes to persuasion.

Feature Engineering For Machine Learning

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Author : Alice Zheng
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-03-23

Feature Engineering For Machine Learning written by Alice Zheng and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-23 with Computers categories.

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques

Advances In Computational Intelligence

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Author : Grigori Sidorov
language : en
Publisher: Springer
Release Date : 2017-08-02

Advances In Computational Intelligence written by Grigori Sidorov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-02 with Computers categories.

The two-volume set LNAI 10061 and 10062 constitutes the proceedings of the 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, held in Cancún, Mexico, in October 2016. The total of 86 papers presented in these two volumes was carefully reviewed and selected from 238 submissions. The contributions were organized in the following topical sections: Part I: natural language processing; social networks and opinion mining; fuzzy logic; time series analysis and forecasting; planning and scheduling; image processing and computer vision; robotics. Part II: general; reasoning and multi-agent systems; neural networks and deep learning; evolutionary algorithms; machine learning; classification and clustering; optimization; data mining; graph-based algorithms; and intelligent learning environments.

Computer Supported Cooperative Work And Social Computing

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Author : Yuqing Sun
language : en
Publisher: Springer Nature
Release Date : 2019-11-13

Computer Supported Cooperative Work And Social Computing written by Yuqing Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-13 with Computers categories.

This book constitutes the refereed proceedings of the 14th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2019, held in Kunming, China, in August 2019. The 52 revised full papers and 10 short papers were carefully reviewed and selected from 169 submissions. The papers of this volume are organized in topical sections on: collaborative models, approaches, algorithms, and systems; social computing (online communities, crowdsourcing, recommendation, sentiment analysis, etc.); AI for CSCW and social computing.