الصفحة 1
الصفحة 1
Ontologies for Agents : Theory and Experiences
On the other hand, ontologies have established themselves as a powerful tool to enable kno- edge sharing, and a growing number of applications have bene?ted from the use of ontologies as a means to achieve semantic interoperability among heterogeneous, distributed systems. In principle ontologies and agents are a match made in heaven, that has failed to happen. What makes a simple piece of software an agent is its ability to communicate in a ”social” environment, to make autonomous decisions, and to be proactive on behalf of its user. Communication ultimately depends on und- standing the goals, preferences, and constraints posed by the user. Autonomy is theabilitytoperformataskwithlittleornouserintervention,whileproactiveness involves acting autonomously with no need for user prompting. Communication, but also autonomy and proactiveness, depend on knowledge. The ability to c- municate depends on understanding the syntax (terms and structure) and the semantics of a language. Ontologies provide the terms used to describe a domain and the semantics associated with them. In addition, ontologies are often comp- mented by some logical rules that constrain the meaning assigned to the terms. These constraints are represented by inference rules that can be used by agents to perform the reasoning on which autonomy and proactiveness are based.
Multiobjective Optimization : Interactive and Evolutionary Approaches
Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support.
Modeling Decisions for Artificial Intelligence ; Vol.3885 ; 3rd International Conference, MDAI 2006, Tarragona, Spain, April 3-5, 2006, Proceedings
This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006.
Handbook of big data analytics ; Vol.2 : Applications in ICT, security and business analytics
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time.
Handbook of big data analytics ; Vol.1 : Methodologies
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. This volume presents several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data.
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.
Designing and evaluating e-management decision tools : The integration of decision and negotiation models into internet-multimedia technologies
Presents the most relevant concepts for designing intelligent decision tools in an Internet-based multimedia environment and assessing the tools using concepts of statistical design of experiments. The book covers : Decision modeling paradigms , Visual interactive decision modeling , Online preference elicitation , collaborative decision making , negotiation and conflict resolution , marketing decision optimization , and guidelines for designing and evaluating decision support tools. This book is designed for the following uses: 1) for researchers and engineers, who are seeking recent advances and who are developing e-management systems; 2) for practitioners and managers, who seek insights about ICT potential and using ICT for business intelligence management; and 3) for students, who seek theoretical and practical concepts of building and evaluating prototype decision tools.
Cooperative Information Agents XI ; Matthias Klusch, Koen V. Hindriks, Mike P. Papazoglou, Leon Sterling
In today’s world of ubiquitously connected heterogeneous information systems and computing devices, the intelligent coordination and provision of relevant added-value information at any time, anywhere is of key importance to a va- ety of applications. This challenge is envisioned to be coped with by means of appropriate intelligent and cooperative information agents. An information agent is a computational software entity that has access to one or multiple heterogeneous and geographically dispersed data and infor- tion sources. It pro-actively searches for and maintains information on behalf of its human users, or other agents preferably just in time. In other words, it is managing and overcoming the di?culties associated with information overload in open, pervasive information and service landscapes. Each component of a modern cooperative information system is represented by an appropriate intelligent information agent capable of resolving system and semantic heterogeneities in a given context on demand. Cooperative infor- tion agents are supposed to accomplish both individual and shared joint goals depending on the actual user preferences in line with given or deduced limits of time, budget and resources available.
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
AI voice dubbing = الدبلجة الصوتية بالذكاء الاصطناعي
The advent of artificial intelligence has revolutionized numerous domains, including media and entertainment. This project focuses on developing an AI Voice Dubbing application that facilitates the seamless dubbing of audio content from English to Arabic. Unlike traditional robotic voice outputs, our application ensures that the dubbed content retains the original voice characteristics, providing a natural and authentic listening experience. The system also offers users the option to select alternative output voices, including those of celebrities, or any other voice by uploading their media, providing a YouTube link, or recording audio directly. The core functionality of the application is to produce a dubbed audio file, maintaining high fidelity to the original speaker's voice tone and style, the application provides a text output of the dubbed content, which users can edit as needed to ensure accuracy and personal preference.
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.
