Natural Language Data Management And Interfaces
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| Author | : Yunyao Li |
| Publisher | : Springer Nature |
| Total Pages | : 136 |
| Release | : 2022-06-01 |
| Genre | : Computers |
| ISBN | : 3031018621 |
The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap. This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research questions, state-of-the-art methods, related systems, and research opportunities and challenges covering both areas. Relevant topics discussed on natural language data management include data models, data sources, queries, storage and indexing, and transforming natural language text. Under natural language interfaces, it presents the anatomy of these interfaces to databases, the challenges related to query understanding and query translation, and relevant aspects of user interactions. Each of the challenges is covered in a systematic way: first starting with a quick overview of the topics, followed by a comprehensive view of recent techniques that have been proposed to address the challenge along with illustrative examples. It also reviews some notable systems in details in terms of how they address different challenges and their contributions. Finally, it discusses open challenges and opportunities for natural language management and interfaces. The goal of this book is to provide an introduction to the methods, problems, and solutions that are used in managing natural language data and building natural language interfaces to databases. It serves as a starting point for readers who are interested in pursuing additional work on these exciting topics in both academic and industrial environments.
| Author | : Yunyao Li |
| Publisher | : Springer Nature |
| Total Pages | : 248 |
| Release | : 2023-11-24 |
| Genre | : Computers |
| ISBN | : 3031450434 |
This book presents a comprehensive overview of Natural Language Interfaces to Databases (NLIDBs), an indispensable tool in the ever-expanding realm of data-driven exploration and decision making. After first demonstrating the importance of the field using an interactive ChatGPT session, the book explores the remarkable progress and general challenges faced with real-world deployment of NLIDBs. It goes on to provide readers with a holistic understanding of the intricate anatomy, essential components, and mechanisms underlying NLIDBs and how to build them. Key concepts in representing, querying, and processing structured data as well as approaches for optimizing user queries are established for the reader before their application in NLIDBs is explored. The book discusses text to data through early relevant work on semantic parsing and meaning representation before turning to cutting-edge advancements in how NLIDBs are empowered to comprehend and interpret human languages. Various evaluation methodologies, metrics, datasets and benchmarks that play a pivotal role in assessing the effectiveness of mapping natural language queries to formal queries in a database and the overall performance of a system are explored. The book then covers data to text, where formal representations of structured data are transformed into coherent and contextually relevant human-readable narratives. It closes with an exploration of the challenges and opportunities related to interactivity and its corresponding techniques for each dimension, such as instances of conversational NLIDBs and multi-modal NLIDBs where user input is beyond natural language. This book provides a balanced mixture of theoretical insights, practical knowledge, and real-world applications that will be an invaluable resource for researchers, practitioners, and students eager to explore the fundamental concepts of NLIDBs.
| Author | : Oscar Castillo |
| Publisher | : Springer |
| Total Pages | : 558 |
| Release | : 2012-09-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3642330215 |
This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.
| Author | : Julia Ann Johnson |
| Publisher | : Regina : Department of Computer Science, University of Regina |
| Total Pages | : 40 |
| Release | : 1991 |
| Genre | : |
| ISBN | : 9780773102040 |
| Author | : Abdul Quamar |
| Publisher | : |
| Total Pages | : 108 |
| Release | : 2022 |
| Genre | : COMPUTERS |
| ISBN | : 9781638280293 |
Natural language interfaces provide an easy way to query and interact with data and enable non-technical users to investigate data sets without the need to know a query language. Recent advances in natural language understanding and processing have resulted in a renewed interest in natural language interfaces to data. The main challenges in natural language querying are identifying the entities involved in the user utterance, connecting the different entities in a meaningful way over the underlying data source to interpret user intents, and generating a structured query. There are two main approaches in the literature for interpreting a user's natural language query. The first are rule-based systems that make use of semantic indices, ontologies, and knowledge graphs to identify the entities in the query, understand the intended relationships between those entities, and utilize grammars to generate the target queries. Second are hybrid approaches that utilize both rule-based techniques as well as deep learning models. Conversational interfaces are the next natural step to one-shot natural language querying by exploiting query context between multiple turns of conversation for disambiguation. In this monograph, the authors review the rule-based and hybrid technologies that are used in natural language interfaces and survey the different approaches to natural language querying. They also describe conversational interfaces for data analytics and discuss several benchmarks used for natural language querying research and evaluation. The monograph concludes with discussion on challenges that need to be addressed before these systems can be widely adopted.
| Author | : Pazos-Rangel, Rodolfo Abraham |
| Publisher | : IGI Global |
| Total Pages | : 554 |
| Release | : 2020-10-02 |
| Genre | : Computers |
| ISBN | : 1799847314 |
Natural language processing (NLP) is a branch of artificial intelligence that has emerged as a prevalent method of practice for a sizeable amount of companies. NLP enables software to understand human language and process complex data that is generated within businesses. In a competitive market, leading organizations are showing an increased interest in implementing this technology to improve user experience and establish smarter decision-making methods. Research on the application of intelligent analytics is crucial for professionals and companies who wish to gain an edge on the opposition. The Handbook of Research on Natural Language Processing and Smart Service Systems is a collection of innovative research on the integration and development of intelligent software tools and their various applications within professional environments. While highlighting topics including discourse analysis, information retrieval, and advanced dialog systems, this book is ideally designed for developers, practitioners, researchers, managers, engineers, academicians, business professionals, scholars, policymakers, and students seeking current research on the improvement of competitive practices through the use of NLP and smart service systems.
| Author | : Jeffrey Xu Yu |
| Publisher | : Springer Nature |
| Total Pages | : 143 |
| Release | : 2022-06-01 |
| Genre | : Technology & Engineering |
| ISBN | : 3031794265 |
It has become highly desirable to provide users with flexible ways to query/search information over databases as simple as keyword search like Google search. This book surveys the recent developments on keyword search over databases, and focuses on finding structural information among objects in a database using a set of keywords. Such structural information to be returned can be either trees or subgraphs representing how the objects, that contain the required keywords, are interconnected in a relational database or in an XML database. The structural keyword search is completely different from finding documents that contain all the user-given keywords. The former focuses on the interconnected object structures, whereas the latter focuses on the object content. The book is organized as follows. In Chapter 1, we highlight the main research issues on the structural keyword search in different contexts. In Chapter 2, we focus on supporting structural keyword search in a relational database management system using the SQL query language. We concentrate on how to generate a set of SQL queries that can find all the structural information among records in a relational database completely, and how to evaluate the generated set of SQL queries efficiently. In Chapter 3, we discuss graph algorithms for structural keyword search by treating an entire relational database as a large data graph. In Chapter 4, we discuss structural keyword search in a large tree-structured XML database. In Chapter 5, we highlight several interesting research issues regarding keyword search on databases. The book can be used as either an extended survey for people who are interested in the structural keyword search or a reference book for a postgraduate course on the related topics. Table of Contents: Introduction / Schema-Based Keyword Search on Relational Databases / Graph-Based Keyword Search / Keyword Search in XML Databases / Other Topics for Keyword Search on Databases
| Author | : Steven Bird |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 506 |
| Release | : 2009-06-12 |
| Genre | : Computers |
| ISBN | : 0596555717 |
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
| Author | : Fouad Sabry |
| Publisher | : One Billion Knowledgeable |
| Total Pages | : 123 |
| Release | : 2023-07-05 |
| Genre | : Computers |
| ISBN | : |
What Is Natural Language User Interface A natural-language user interface is a sort of computer human interface in which linguistic phenomena such as verbs, phrases, and clauses operate as UI controllers for the purpose of producing, selecting, and changing data in software programs. Natural-language user interfaces are becoming increasingly popular. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Natural-language user interface Chapter 2: List of artificial intelligence projects Chapter 3: Natural-language understanding Chapter 4: Question answering Chapter 5: Document retrieval Chapter 6: Outline of natural language processing Chapter 7: Concept search Chapter 8: Natural-language programming Chapter 9: Google Hummingbird Chapter 10: Query understanding (II) Answering the public top questions about natural language user interface. (III) Real world examples for the usage of natural language user interface in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of natural language user interface' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of natural language user interface.
| Author | : United States. Congress. Office of Technology Assessment |
| Publisher | : Office of Technology Assessment |
| Total Pages | : 468 |
| Release | : 1992 |
| Genre | : Science |
| ISBN | : |
