Fashion Recommender Systems

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Fashion Recommender Systems

Author : Nima Dokoohaki
Publisher : Springer Nature
ISBN 13 : 3030552187
Total Pages : 144 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Fashion Recommender Systems by : Nima Dokoohaki

Download or read book Fashion Recommender Systems written by Nima Dokoohaki and published by Springer Nature. This book was released on 2020-11-04 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the first workshop on Recommender Systems in Fashion 2019. It presents a state of the art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail and fashion. The volume covers contributions from academic as well as industrial researchers active within this emerging new field. Recommender Systems are often used to solve different complex problems in this scenario, such as social fashion-based recommendations (outfits inspired by influencers), product recommendations, or size and fit recommendations. The impact of social networks and the influence that fashion influencers have on the choices people make for shopping is undeniable. For instance, many people use Instagram to learn about fashion trends from top influencers, which helps them to buy similar or even exact outfits from the tagged brands in the post. When traced, customers’ social behavior can be a very useful guide for online shopping websites, providing insights on the styles the customers are really interested in, and hence aiding the online shops in offering better recommendations and facilitating customers quest for outfits. Another well known difficulty with recommendation of similar items is the large quantities of clothing items which can be considered similar, but belong to different brands. Relying only on implicit customer behavioral data will not be sufficient in the coming future to distinguish between for recommendation that will lead to an item being purchased and kept, vs. a recommendation that might result in either the customer not following it, or eventually return the item. Finding the right size and fit for clothes is one of the major factors not only impacting customers purchase decision, but also their satisfaction from e-commerce fashion platforms. Moreover, fashion articles have important sizing variations. Finally, customer preferences towards perceived article size and fit for their body remain highly personal and subjective which influences the definition of the right size for each customer. The combination of the above factors leaves the customers alone to face a highly challenging problem of determining the right size and fit during their purchase journey, which in turn has resulted in having more than one third of apparel returns to be caused by not ordering the right article size. This challenge presents a huge opportunity for research in intelligent size and fit recommendation systems and machine learning solutions with direct impact on both customer satisfaction and business profitability.

Recommender Systems in Fashion and Retail

Author : Nima Dokoohaki
Publisher : Springer
ISBN 13 : 9783030661052
Total Pages : 160 pages
Book Rating : 4.6/5 (61 download)

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Book Synopsis Recommender Systems in Fashion and Retail by : Nima Dokoohaki

Download or read book Recommender Systems in Fashion and Retail written by Nima Dokoohaki and published by Springer. This book was released on 2022-03-24 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, or size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).

Recommender Systems

Author : Dietmar Jannach
Publisher : Cambridge University Press
ISBN 13 : 1139492594
Total Pages : pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Recommender Systems by : Dietmar Jannach

Download or read book Recommender Systems written by Dietmar Jannach and published by Cambridge University Press. This book was released on 2010-09-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems.

Explainable Recommendation

Author : Yongfeng Zhang
Publisher :
ISBN 13 : 9781680836585
Total Pages : 114 pages
Book Rating : 4.8/5 (365 download)

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Book Synopsis Explainable Recommendation by : Yongfeng Zhang

Download or read book Explainable Recommendation written by Yongfeng Zhang and published by . This book was released on 2020-03-10 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, a large number of explainable recommendation approaches have been proposed and applied in real-world systems. This survey provides a comprehensive review of the explainable recommendation research.

Recommender Systems

Author : Charu C. Aggarwal
Publisher : Springer
ISBN 13 : 3319296590
Total Pages : 518 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Recommender Systems by : Charu C. Aggarwal

Download or read book Recommender Systems written by Charu C. Aggarwal and published by Springer. This book was released on 2016-03-28 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.

Generative Adversarial Networks for Image-to-Image Translation

Author : Arun Solanki
Publisher : Academic Press
ISBN 13 : 0128236132
Total Pages : 446 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Generative Adversarial Networks for Image-to-Image Translation by : Arun Solanki

Download or read book Generative Adversarial Networks for Image-to-Image Translation written by Arun Solanki and published by Academic Press. This book was released on 2021-06-22 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images. - Introduces the concept of Generative Adversarial Networks (GAN), including the basics of Generative Modelling, Deep Learning, Autoencoders, and advanced topics in GAN - Demonstrates GANs for a wide variety of applications, including image generation, Big Data and data analytics, cloud computing, digital transformation, E-Commerce, and Artistic Neural Networks - Includes a wide variety of biomedical and scientific applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing, and disease diagnosis - Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable GANs for their applications

Collaborative Filtering Recommender Systems

Author : Michael D. Ekstrand
Publisher : Now Publishers Inc
ISBN 13 : 1601984421
Total Pages : 104 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Collaborative Filtering Recommender Systems by : Michael D. Ekstrand

Download or read book Collaborative Filtering Recommender Systems written by Michael D. Ekstrand and published by Now Publishers Inc. This book was released on 2011 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Hands-On Recommendation Systems with Python

Author : Rounak Banik
Publisher : Packt Publishing Ltd
ISBN 13 : 1788992539
Total Pages : 141 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On Recommendation Systems with Python by : Rounak Banik

Download or read book Hands-On Recommendation Systems with Python written by Rounak Banik and published by Packt Publishing Ltd. This book was released on 2018-07-31 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Key Features Build industry-standard recommender systems Only familiarity with Python is required No need to wade through complicated machine learning theory to use this book Book Description Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains. What you will learn Get to grips with the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content based engine to recommend movies based on movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative fltering Who this book is for If you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.

Recommender Systems in Fashion and Retail

Author : Nima Dokoohaki
Publisher : Springer Nature
ISBN 13 : 3030661032
Total Pages : 160 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Recommender Systems in Fashion and Retail by : Nima Dokoohaki

Download or read book Recommender Systems in Fashion and Retail written by Nima Dokoohaki and published by Springer Nature. This book was released on 2021-03-23 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, or size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).

Recommender Systems Handbook

Author : Francesco Ricci
Publisher : Springer
ISBN 13 : 148997637X
Total Pages : 1008 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Recommender Systems Handbook by : Francesco Ricci

Download or read book Recommender Systems Handbook written by Francesco Ricci and published by Springer. This book was released on 2015-11-17 with total page 1008 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

Recommender Systems in Fashion and Retail

Author : Humberto Jesús Corona Pampín
Publisher : Springer Nature
ISBN 13 : 3031221923
Total Pages : 125 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Recommender Systems in Fashion and Retail by : Humberto Jesús Corona Pampín

Download or read book Recommender Systems in Fashion and Retail written by Humberto Jesús Corona Pampín and published by Springer Nature. This book was released on 2023-03-01 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the fourth workshop on recommender systems in fashion and retail (2022), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).

Recommender Systems Handbook

Author : Francesco Ricci
Publisher : Springer Nature
ISBN 13 : 1071621971
Total Pages : 1053 pages
Book Rating : 4.0/5 (716 download)

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Book Synopsis Recommender Systems Handbook by : Francesco Ricci

Download or read book Recommender Systems Handbook written by Francesco Ricci and published by Springer Nature. This book was released on 2022-04-21 with total page 1053 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.

Emerging Technology in Modelling and Graphics

Author : Jyotsna Kumar Mandal
Publisher : Springer
ISBN 13 : 9811374031
Total Pages : 782 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Emerging Technology in Modelling and Graphics by : Jyotsna Kumar Mandal

Download or read book Emerging Technology in Modelling and Graphics written by Jyotsna Kumar Mandal and published by Springer. This book was released on 2019-07-16 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers cutting-edge and advanced research in modelling and graphics. Gathering high-quality papers presented at the First International Conference on Emerging Technology in Modelling and Graphics, held from 6 to 8 September 2018 in Kolkata, India, it addresses topics including: image processing and analysis, image segmentation, digital geometry for computer imaging, image and security, biometrics, video processing, medical imaging, and virtual and augmented reality.

HCI International 2020 - Posters

Author : Constantine Stephanidis
Publisher : Springer Nature
ISBN 13 : 3030507262
Total Pages : 739 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis HCI International 2020 - Posters by : Constantine Stephanidis

Download or read book HCI International 2020 - Posters written by Constantine Stephanidis and published by Springer Nature. This book was released on 2020-07-11 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set CCIS 1224, CCIS 1225, and CCIS 1226 contains the extended abstracts of the posters presented during the 22nd International Conference on Human-Computer Interaction, HCII 2020, which took place in Copenhagen, Denmark, in July 2020.* HCII 2020 received a total of 6326 submissions, of which 1439 papers and 238 posters were accepted for publication in the pre-conference proceedings after a careful reviewing process. The 238 papers presented in these three volumes are organized in topical sections as follows: Part I: design and evaluation methods and tools; user characteristics, requirements and preferences; multimodal and natural interaction; recognizing human psychological states; user experience studies; human perception and cognition. -AI in HCI. Part II: virtual, augmented and mixed reality; virtual humans and motion modelling and tracking; learning technology. Part III: universal access, accessibility and design for the elderly; smartphones, social media and human behavior; interacting with cultural heritage; human-vehicle interaction; transport, safety and crisis management; security, privacy and trust; product and service design. *The conference was held virtually due to the COVID-19 pandemic.

Practical Recommender Systems

Author : Kim Falk
Publisher : Simon and Schuster
ISBN 13 : 1638353980
Total Pages : 743 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Practical Recommender Systems by : Kim Falk

Download or read book Practical Recommender Systems written by Kim Falk and published by Simon and Schuster. This book was released on 2019-01-18 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Online recommender systems help users find movies, jobs, restaurants-even romance! There's an art in combining statistics, demographics, and query terms to achieve results that will delight them. Learn to build a recommender system the right way: it can make or break your application! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions. Recommender systems are practically a necessity for keeping your site content current, useful, and interesting to your visitors. About the Book Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you'll encounter as your site grows. What's inside How to collect and understand user behavior Collaborative and content-based filtering Machine learning algorithms Real-world examples in Python About the Reader Readers need intermediate programming and database skills. About the Author Kim Falk is an experienced data scientist who works daily with machine learning and recommender systems. Table of Contents PART 1 - GETTING READY FOR RECOMMENDER SYSTEMS What is a recommender? User behavior and how to collect it Monitoring the system Ratings and how to calculate them Non-personalized recommendations The user (and content) who came in from the cold PART 2 - RECOMMENDER ALGORITHMS Finding similarities among users and among content Collaborative filtering in the neighborhood Evaluating and testing your recommender Content-based filtering Finding hidden genres with matrix factorization Taking the best of all algorithms: implementing hybrid recommenders Ranking and learning to rank Future of recommender systems

Group Recommender Systems

Author : Alexander Felfernig
Publisher : Springer Nature
ISBN 13 : 3031449436
Total Pages : 180 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Group Recommender Systems by : Alexander Felfernig

Download or read book Group Recommender Systems written by Alexander Felfernig and published by Springer Nature. This book was released on 2023-11-27 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses different aspects of group recommender systems, which are systems that help to identify recommendations for groups instead of single users. In this context, the authors present different related techniques and applications. The book includes in-depth summaries of group recommendation algorithms, related industrial applications, different aspects of preference construction and explanations, user interface aspects of group recommender systems, and related psychological aspects that play a crucial role in group decision scenarios.

Artificial Intelligence on Fashion and Textiles

Author : Wai Keung Wong
Publisher : Springer
ISBN 13 : 3319996959
Total Pages : 329 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Artificial Intelligence on Fashion and Textiles by : Wai Keung Wong

Download or read book Artificial Intelligence on Fashion and Textiles written by Wai Keung Wong and published by Springer. This book was released on 2018-10-13 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book includes the Proceedings of the Artificial Intelligence on Fashion and Textiles conference 2018 which provides state-of-the-art techniques and applications of AI in the fashion and textile industries. It is essential reading for scientists, researchers and R&D professionals working in the field of AI with applications in the fashion and textile industry; managers in the fashion and textile enterprises; and anyone with an interest in the applications of AI. Over the last two decades, with the great advancement of computer technology, academic research in artificial intelligence (AI) and its applications in fashion and textile supply chain has been becoming a very hot topic and has received greater attention from both academics and industrialists. A number of AI-related techniques has been successfully employed and proven to handle the problems including fashion sales forecasting, supply chain optimization, planning and scheduling, textile material defect detection, fashion and textile image recognition, fashion image and style retrieval, human body modeling and fitting, etc.