Computational Intelligence for Information Retrieval


Book Description

This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human–computer interaction is the motivation behind this book. The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies. Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.




Emerging Artificial Intelligence Applications in Computer Engineering


Book Description

Provides insights on how computer engineers can implement artificial intelligence (AI) in real world applications. This book presents practical applications of AI.




Mastering the RAG: A Practical Guide to Deploying AI-Powered Data Retrieval and Generation in Your Enterprise -ERP, SAP, SFDC


Book Description

Mastering the RAG: Unleash the Power of AI in Your Enterprise Mastering the RAG: A Practical Guide to Deploying AI-Powered Data Retrieval and Generation in Your Enterprise (ERP, SAP, SFDC) equips you to harness the transformative power of Retrieval-Augmented Generation (RAG) for your enterprise applications. This book is your one-stop guide to implementing RAG with industry leaders like Oracle ERP, SAP, and Salesforce (SFDC), unlocking new levels of efficiency and data-driven insights. Imagine a world where AI streamlines your workflows, intelligently retrieves data from your core enterprise applications, and generates comprehensive reports or creative text formats at your command. That's the power of RAG. This practical guide takes you step-by-step through the entire deployment process, from selecting the right Large Language Model (LLM) to building a user-friendly interface. Part 1: Unveiling the RAG Potential Demystify the RAG pattern: Grasp the core concepts and how it revolutionizes data retrieval and generation within enterprise applications. Discover the advantages: Explore the tangible benefits of RAG for ERP, SAP, and SFDC users, including faster information retrieval, improved report generation, and enhanced automation. Identify use cases: Learn how RAG can be applied to real-world scenarios across various departments, from generating sales forecasts in SFDC to creating comprehensive financial reports in Oracle ERP. Part 2: Charting Your RAG Implementation Journey Prepare for deployment: Understand the necessary pre-requisites, including identifying compatible data sources within your enterprise applications and choosing the most suitable LLM for your specific needs. Dive deep into implementation: This section provides a detailed roadmap for setting up the retrieval component, integrating the LLM, and building a user-friendly interface or chatbot for seamless interaction. Security matters: Learn best practices for safeguarding sensitive enterprise data throughout the RAG deployment process. Part 3: Optimizing and Refining Your RAG Perfecting performance: Discover techniques for testing and evaluating your RAG system to ensure accuracy, mitigate bias, and promote explainability. User feedback and iteration: Learn how to incorporate user feedback into continuous improvement cycles to refine your RAG and maximize its effectiveness. Mastering the RAG empowers you to become a leader in adopting cutting-edge AI solutions within your enterprise. This book equips you with the knowledge and practical steps to unlock a new era of data-driven decision making and streamline workflows across Oracle ERP, SAP, and SFDC




Introduction to Information Retrieval


Book Description

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.




Deep Natural Language Processing and AI Applications for Industry 5.0


Book Description

To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.




Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough


Book Description

This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.




Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots


Book Description

This monograph is the first survey of neural approaches to conversational AI that targets Natural Language Processing and Information Retrieval audiences. It provides a comprehensive survey of the neural approaches to conversational AI that have been developed in the last few years, covering QA, task-oriented and social bots with a unified view of optimal decision making.The authors draw connections between modern neural approaches and traditional approaches, allowing readers to better understand why and how the research has evolved and to shed light on how they can move forward. They also present state-of-the-art approaches to training dialogue agents using both supervised and reinforcement learning. Finally, the authors sketch out the landscape of conversational systems developed in the research community and released in industry, demonstrating via case studies the progress that has been made and the challenges that are still being faced.Neural Approaches to Conversational AI is a valuable resource for students, researchers, and software developers. It provides a unified view, as well as a detailed presentation of the important ideas and insights needed to understand and create modern dialogue agents that will be instrumental to making world knowledge and services accessible to millions of users in ways that seem natural and intuitive.




Applying AI-Based IoT Systems to Simulation-Based Information Retrieval


Book Description

Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.




Advances in Information Retrieval


Book Description

The three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration papers, 12 reproducibility papers consortium papers, 7 tutorial papers, and 10 doctorial consortium papers were carefully reviewed and selected from 489 submissions. The book also contains, 8 workshop summaries and 13 CLEF Lab descriptions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.




Information Representation and Retrieval in the Digital Age


Book Description

Information representation and retrieval : an overview -- Information representation I : basic approaches -- Information representation II : other related topics -- Language in information representation and retrieval -- Retrieval techniques and query representation -- Retrieval approaches -- Information retrieval models -- Information retrieval systems -- Retrieval of information unique in content or format -- The user dimension in information representation and retrieval -- Evaluation of information representation and retrieval -- Artificial intelligence in information representation and retrieval.