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Author: Yongfeng Zhang
Publisher:
ISBN: 9781680836585
Category : Computers
Languages : en
Pages : 114
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Book Description
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.
Author: Yongfeng Zhang
Publisher:
ISBN: 9781680836585
Category : Computers
Languages : en
Pages : 114
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Book Description
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.
Author: Dongsheng Li
Publisher: Springer Nature
ISBN: 9819989647
Category :
Languages : en
Pages : 292
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Book Description
Author: Norbert A. Streitz
Publisher: Springer Nature
ISBN: 3031600126
Category :
Languages : en
Pages : 473
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Book Description
Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Computers
Languages : en
Pages : 320
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Book Description
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Author: B. K. Tripathy
Publisher: CRC Press
ISBN: 1040099939
Category : Technology & Engineering
Languages : en
Pages : 355
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Book Description
Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case studies, latest techniques, and applications from domains such as healthcare, finance, and network security. It also covers open-source interpretable tool kits so that practitioners can use them in their domains. Features: Presents a clear focus on the application of explainable AI systems while tackling important issues of “interpretability” and “transparency”. Reviews adept handling with respect to existing software and evaluation issues of interpretability. Provides insights into simple interpretable models such as decision trees, decision rules, and linear regression. Focuses on interpreting black box models like feature importance and accumulated local effects. Discusses capabilities of explainability and interpretability. This book is aimed at graduate students and professionals in computer engineering and networking communications.
Author: Arnab Bhattacharya
Publisher: Springer Nature
ISBN: 3031001265
Category : Computers
Languages : en
Pages : 744
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Book Description
The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.
Author: Fernando De La Prieta
Publisher: Springer Nature
ISBN: 3030857107
Category : Computers
Languages : en
Pages : 324
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Book Description
This book constitutes the proceedings of the workshops co-located with the 19th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021, held in Salamanca, Spain, in October 2021. The total of 17 full and 9 short papers presented in this volume were carefully selected from 42 submissions. The papers in this volume stem from the following meetings:Workshop on Character Computing (C2); Workshop on Deep Learning Applications (DeLA); Workshop on Decision Support, Recommendation, and Persuasion in Artificial Intelligence (DeRePAI); Workshop on Multi-agent based Applications for Modern Energy Markets, Smart Grids and Future Power Systems (MASGES); Workshop on Smart Cities and Intelligent Agents (SCIA).
Author: Guojun Wang
Publisher: Springer Nature
ISBN: 3030600297
Category : Computers
Languages : en
Pages : 674
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Book Description
This book constitutes the proceedings of the 17th International Conference on Web Information Systems and Applications, WISA 2020, held in Guangzhou, China, in September 2020. The 42 full papers and 16 short papers presented were carefully reviewed and selected from 165 submissions. The papers are grouped in topical sections on world wide web, recommendation, query processing and algorithm, natural language processing, machine learning, graph query, edge computing and data mining, data privacy and security, and blockchain.
Author: Tom Rutkowski
Publisher: Springer Nature
ISBN: 3030755215
Category : Technology & Engineering
Languages : en
Pages : 167
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Book Description
The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. The vast majority of AI models work like black box models. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations. Therefore, the development of artificial intelligence cannot ignore the need for interpretable, transparent, and explainable models. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems. In turn, various novel recommenders are proposed, each characterized by achieving high accuracy with a reasonable number of interpretable fuzzy rules. The main part of the book is devoted to a very challenging problem of stock market recommendations. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers.
Author: Christian S. Jensen
Publisher: Springer Nature
ISBN: 3030732002
Category : Computers
Languages : en
Pages : 677
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Book Description
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.
