Mobile Service Computing
This book introduces readers to the background and principles of mobile service computing. It discusses various aspects of service computing in mobile environments, including key methods and techniques for service selection, recommendation, composition, offloading, execution, deployment, and provision.
Metalearning : Applications to Automated Machine Learning and Data Mining
This book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user.
Green, pervasive, and cloud computing ; 15th International conference, GPC 2020, Xi'an, China, November 13–15, 2020, Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020, held in Xi'an, China, in November 2020. The 30 full papers presented in this book together with 8 short papers were carefully reviewed and selected from 96 submissions. They cover the following topics: Device-free Sensing; Machine Learning; Recommendation Systems; Urban Computing; Human Computer Interaction; Internet of Things and Edge Computing; Positioning; Applications of Computer Vision; CrowdSensing; and Cloud and Related Technologies.
Food lens = فود لينس
Food lens is an innovative application designed to revolutionize dietary management by leveraging advanced image recognition and nutritional analysis. The primary objective of this senior project is to develop a user-friendly tool that identifies various foods through a camera interface and provides detailed nutritional information. This application not only enhances the user's understanding of their dietary intake but also assists in achieving personalized health and fitness goals. The core functionality of Food Lens involves the integration of a robust image recognition system capable of accurately identifying a wide range of foods. Upon identification, the application retrieves comprehensive nutritional data, including calorie content, macronutrient distribution (proteins, fats, carbohydrates), and essential micronutrients (vitamins and minerals). This data is then seamlessly integrated into the user's dietary profile. Food Lens is designed to track the user's daily caloric intake and compare it against personalized recommendations based on age, gender, weight, height, and activity level. By maintaining a dynamic record of consumed foods, the application provides real-time feedback on the user’s nutritional progress. This feature is particularly beneficial for individuals aiming to manage weight, address dietary restrictions, or improve overall health.
Fashionity
This project is an AI fashion design system to generate fashion images based on user textual description. The proposed system incorporates advanced technology for dissemination and machine translation with the aim of facilitating a seamless user experience for input in both Arabic and English languages. Moreover, the project encompasses the incorporation of a recommendation system that proposes appropriate visual content based on user style. The primary objective of this project is to develop a robust framework capable of generating high-quality images based on textual descriptions, providing recommendations for similar clothing items, and facilitating the retrieval of photographic and apparel articles through image search.
Fashion forge
"Fashion forge" revolutionizes clothing shopping with a cutting-edge mobile application. This AI-powered platform empowers users to describe their dream garment and visualize it instantly, bridging the gap between imagination and reality for fashion-forward users and designers. A recommendation system tailors clothing suggestions based on user preferences, while stores leverage a dedicated social platform for effective marketing. "Fashion Forge" fosters a connected fashion community, empowering users, designers, and stores alike.
Enterprise service oriented architectures : Concepts, challenges, recommendations
Enterprise Service Oriented Architectures helps readers solve this challenge in making different applications communicate in a loosely coupled manner. This classic handbook leverages the experiences of thought leaders functioning in multiple industry verticals and provides a wealth of knowledge for creating the agile enterprise.
Deep Learning and its Applications
Presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction.
Database performance at scale: a practical guide
Optimizing database performance at the scale required for today’s data-intensive applications often requires more than performance tuning and scaling out. This book shares commonly overlooked considerations, pitfalls, and opportunities that have helped many teams break through database performance plateaus. It’s neither a definitive guide to distributed databases nor a beginner’s resource. Rather, it’s a look at the many different factors that impact performance, and our top field-tested recommendations for navigating them. Chapter 1 provides two (fun and fanciful) tales that surface some of the many roadblocks you might face and highlight the range of strategies for navigating around them.
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Knowledge science, engineering and management; 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I
Constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning.
Knowledge science, engineering and management ; 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part II
Constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning.
Big Data Recommender Systems ; Vol.2 : Application Paradigms
Combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools. First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges. recommender systems. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters
Becoming a teacher educator : Theory and practice for teacher educators
It is the first book that addresses a range of important topics related to the work of teacher educators, the induction of teacher educators and their further professional development.Becoming a Teacher Educator has a practical focus and it provides theoretical insights, experiences of experts and practical recommendations. The book is rooted in the Association of Teacher Education in Europe (ATEE) and many of the chapters are written by authors who are active members of the ATEE. Distinguished researchers and practitioners from different parts of Europe, and beyond, joined their efforts to write a book that is truly international and combines research, practice and reflection.
AI journal submitting = تقديم المقالات بالذكاء الصنعي
Aims to develop a comprehensive platform to support academic writers in preparing their research papers in word file format, adhering to the Damascus University template. The platform leverages advanced artificial intelligence techniques to offer services such as grammatical and spelling correction, plagiarism detection, and citation analysis. It also provides comprehensive evaluation tools for peer reviewers, facilitating accurate and reliable feedback.The platform consists of four main components: • User Interface for Creating and Formatting Papers: Simplifies the entry and automatic formatting of texts according to the Damascus University template. / • Intelligent Language Correction System: Utilizes natural language processing techniques to enhance language quality and clarity. / • Citation Analysis and Plagiarism Detection Tool: Identifies improper citations and provides detailed reports on copied sections. / • Peer Review Support System: Offers advanced evaluation tools and AI-driven analytical reports for reviewers.This platform aims to improve the quality and integrity of academic research, streamline the formatting process, and enhance the efficiency of the peer review process, thereby elevating the level of scientific output at Damascus University.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
Advances in web mining and web usage analysis ; 6th International workshop on knowledge discovery on the web, WEBKDD 2004, Seattle, WA, USA, August 22-25, 2004, Revised Selected Papers
The Webisaliveenvironmentthatmanagesanddrivesawidespectrumofapp- cations in which a user may interact with a company, a governmental authority, a non-governmental organization or other non-pro?t institution or other users. User preferences and expectations, together with usage patterns, form the basis for personalized, user-friendly and business-optimal services. Key Web business metrics enabled by proper data capture and processing are essential to run an e?ective business or service. Enabling technologies include data mining, sc- able warehousing and preprocessing, sequence discovery, real time processing, document classi?cation, user modeling and quality evaluation models for them. Recipient technologies required for user pro?ling and usage patterns include recommendation systems, Web analytics applications, and application servers, coupled with content management systems and fraud detectors.
Advances in information retrieval ; 29th European Conference on IR Research, ECIR 2007, Rome, Italy, April 2-5, 2007, Proceedings
This book presented evaluation, recommendation, optimization, semantics, aggregation, queries, mining social media, digital libraries, efficiency, and information retrieval theory. Also included are 3 tutorial and 4 workshop presentations.
Advances in Data Mining : Applications in E-Commerce, Medicine, and Knowledge Management
Presents papers describing selected projects on the topic of data mining in fields like e commerce, medicine, and knowledge management. The objective is to report on current results and at the same time to give a review on the present activities in this field in Germany. An effort has been made to include the latest scientific results, as well as lead the reader to the various fields of activity and the problems related to them. Knowledge discovery on the basis of web data is a wide and fast growing area. E commerce is the principal theme of motivation in this field, as companies invest large sums in the electronic market, in order to maximize their profits and minimize their risks. Other applications are telelearning, teleteaching, service support, and citizen information systems. Concerning these applications, there is a great need to understand and support the user by means of recommendation systems, adaptive information systems, as well as by personalization.
Advancement of Deep Learning and its Applications in Object Detection and Recognition
In just the past five years, deep learning has taken the world by surprise, driving rapid progress in fields as diverse as computer vision, natural language processing, automatic speech recognition, etc. This book presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction.



















