Algorithmic Reading Comprehension
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Machine Reading Comprehension
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Author : Chenguang Zhu
language : en
Publisher: Elsevier
Release Date : 2021-03-20
Machine Reading Comprehension written by Chenguang Zhu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-20 with Computers categories.
Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing. Presents the first comprehensive resource on machine reading comprehension (MRC) Performs a deep-dive into MRC, from fundamentals to latest developments Offers the latest thinking and research in the field of MRC, including the BERT model Provides theoretical discussion, code analysis, and real-world applications of MRC Gives insight from research which has led to surpassing human parity in MRC
Algorithmic Reading Comprehension
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Author : Rahul Anand
language : en
Publisher: Educreation Publishing
Release Date : 2018-10-10
Algorithmic Reading Comprehension written by Rahul Anand and has been published by Educreation Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-10 with Education categories.
Reading comprehension solving is a skill. It is different from literature in the sense that it is independent of interpretation. There is no subjectivity in RC questions. The art of solving can be learnt by mastering the topic at three levels – The ability to read, to eliminate options and to build mistake patterns to learn from them. These three levels lie at the core of "Algorithmic Reading Comprehension" – an approach to build expertise in RC solving. This approach was created by my team and me over the past 6 years of training thousands of students for the Reading comprehension section for CAT-GMAT and other aptitude-based entrance examinations. The book deals with two major aspects of reading, "Central Idea" and "Contextual Word Learning". It moves on to discuss the meaning of different question types asked across exams and provides elimination frameworks to tackle tricky options. Finally, students get many passages arranged in levels and then in a practice chapter to practice and to learn from. Welcome to the world of flawless RC learning!
The Psychology Of Learning And Motivation
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Author :
language : en
Publisher: Academic Press
Release Date : 2010-02-05
The Psychology Of Learning And Motivation written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-05 with Psychology categories.
The Psychology of Learning and Motivation series publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning to complex learning and problem solving. Each chapter thoughtfully integrates the writings of leading contributors, who present and discuss significant bodies of research relevant to their discipline. Volume 51 includes chapters on such varied topics as emotion and memory interference, electrophysiology, mathematical cognition, and reader participation in narrative. Volume 51 of the highly regarded Psychology of Learning and Motivation series An essential reference for researchers and academics in cognitive science Relevant to both applied concerns and basic research
Algorithmic Thinking
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Author : Daniel Zingaro
language : en
Publisher: No Starch Press
Release Date : 2020-12-15
Algorithmic Thinking written by Daniel Zingaro and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-15 with Computers categories.
A hands-on, problem-based introduction to building algorithms and data structures to solve problems with a computer. Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems. Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like: The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations The union-find data structure to answer questions about connections in a social network or determine who are friends or enemies The heap data structure to determine the amount of money given away in a promotion The hash-table data structure to determine whether snowflakes are unique or identify compound words in a dictionary NOTE: Each problem in this book is available on a programming-judge website. You'll find the site's URL and problem ID in the description. What's better than a free correctness check?
Algorithmic Thinking 2nd Edition
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Author : Daniel Zingaro
language : en
Publisher: No Starch Press
Release Date : 2024-01-23
Algorithmic Thinking 2nd Edition written by Daniel Zingaro and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-23 with Computers categories.
Get in the game and learn essential computer algorithms by solving competitive programming problems, in the fully revised second edition of the bestselling original. (Still no math required!) Are you hitting a wall with data structures and algorithms? Whether you’re a student prepping for coding interviews or an independent learner, this book is your essential guide to efficient problem-solving in programming. UNLOCK THE POWER OF DATA STRUCTURES & ALGORITHMS: Learn the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge. REAL-WORLD, COMPETITION-PROVEN CODE EXAMPLES: The programs and challenges in this book aren’t just theoretical—they’re drawn from real programming competitions. Train with problems that have tested and honed the skills of coders around the world. GET INTERVIEW-READY: Prepare yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently. WRITTEN IN C, USEFUL ACROSS LANGUAGES: The code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem: We’ve got recommended reading, too. Algorithmic Thinking is the complete package, providing the solid foundation you need to elevate your coding skills to the next level.
Advances In Information And Communication
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Author : Kohei Arai
language : en
Publisher: Springer Nature
Release Date : 2020-02-13
Advances In Information And Communication written by Kohei Arai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-13 with Technology & Engineering categories.
This book presents high-quality research on the concepts and developments in the field of information and communication technologies, and their applications. It features 134 rigorously selected papers (including 10 poster papers) from the Future of Information and Communication Conference 2020 (FICC 2020), held in San Francisco, USA, from March 5 to 6, 2020, addressing state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of future research. Discussing various aspects of communication, data science, ambient intelligence, networking, computing, security and Internet of Things, the book offers researchers, scientists, industrial engineers and students valuable insights into the current research and next generation information science and communication technologies.
A Computational Mimicry Of The Knowledge Augmentation Process In Comprehension Based Learning
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Author : Amal Babour
language : en
Publisher:
Release Date : 2017
A Computational Mimicry Of The Knowledge Augmentation Process In Comprehension Based Learning written by Amal Babour and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Reading categories.
Reading is one of the most dominate means of modern human learning. The process of reading comprehension has long been studied in psychology, yet no algorithm level model for comprehension is available to-date. In this thesis, we explore a plausible computational model behind a difficult form of comprehension- prose comprehension. We define prose as a sophisticated text rich with complex concepts that has specialized meanings and associations that are subtle, and in general difficult to comprehended from the prose alone. Thus a prose text needs the use of external knowledge or references to comprehend. Readers always breakdown the text into concepts and create knowledge associations among them in a graph. Thus the knowledge space of a prose is represented as disconnected subgraphs with multiple components. We postulate a comprehension engine consisting of two major cognitive processes involved; knowledge induction and distillation. The induction process seeks to connect the knowledge space in particular augmenting the associations by incremental reading external reference texts, finding the highest familiarity knowledge associations among the prose concepts. It also uses ontology engine to find lexical knowledge associations among pairs of concepts. The objective is to obtain a knowledge space graph with single giant component to establish a base model for the prose comprehension. We experiment using a version of Steiner Tree called Terminal-to-Terminal Steiner Tree (TTST) that mimics finding the highest familiarity knowledge associations (links) among the prose concepts through no or minimum number of external concepts. The time complexity of the algorithm is O(C+E). The knowledge distillation process is a reduction process on the connected knowledge space graph. It grades the knowledge associations pathways in the connected knowledge space and selects a set of associations that most helps the comprehension for without overwhelming the cognitive capacity. We suggest to use a novel graph grading scheme based on equivalent electrical circuit (EEC) theory for grading the knowledge associations where the highest delivered current flow between the two concepts can mimic the comprehension efficiency of association pathways in the knowledge space graph. To evaluate the proposed comprehension engine, we conduct an experiment with various selected proses. Similar to human readers, we let the comprehension engine mine reference texts from modern knowledge corpuses Wikipedia and Wordnet. For the experiment, we use Gutenberg Project word frequency data to assign familiarity indexes needed in these algorithms. We measure knowledge gain of human readers at pre-comprehension and post-comprehension stages. The results of the experiment verify the potential efficiency of using comprehension engine for improving the quality of human comprehension and saving time.
Algorithmic Intimacy
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Author : Anthony Elliott
language : en
Publisher: John Wiley & Sons
Release Date : 2022-10-11
Algorithmic Intimacy written by Anthony Elliott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-11 with Social Science categories.
Artificial intelligence not only powers our cars, hospitals and courtrooms: predictive algorithms are becoming deeply lodged inside us too. Machine intelligence is learning our private preferences and discreetly shaping our personal behaviour, telling us how to live, who to befriend and who to date. In Algorithmic Intimacy, Anthony Elliott examines the power of predictive algorithms in reshaping personal relationships today. From Facebook friends and therapy chatbots to dating apps and quantified sex lives, Elliott explores how machine intelligence is working within us, amplifying our desires and steering our personal preferences. He argues that intimate relationships today are threatened not by the digital revolution as such, but by the orientation of various life strategies unthinkingly aligned with automated machine intelligence. Our reliance on algorithmic recommendations, he suggests, reflects a growing emergency in personal agency and human bonds. We need alternatives, innovation and experimentation for the interpersonal, intimate effort of ongoing translation back and forth between the discourses of human and machine intelligence. Accessible and compelling, this book sheds fresh light on the impact of artificial intelligence on the most intimate aspects of our lives. It will appeal to students in the social sciences and humanities and to a wide range of general readers.
Writing Futures Collaborative Algorithmic Autonomous
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Author : Ann Hill Duin
language : en
Publisher: Springer Nature
Release Date : 2021-06-18
Writing Futures Collaborative Algorithmic Autonomous written by Ann Hill Duin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-18 with Technology & Engineering categories.
This book is useful to understand and write alongside non-human agents, examine the impact of algorithms and AI on writing, and accommodate relationships with autonomous agents. This ground-breaking future-driven framework prepares scholars and practitioners to investigate and plan for the social, digital literacy, and civic implications arising from emerging technologies. This book prepares researchers, students, practitioners, and citizens to work with AI writers, virtual humans, and social robots. This book explores prompts to envision how fields and professions will change. The book’s unique integration with Fabric of Digital Life, a database and structured content repository for conducting social and cultural analysis of emerging technologies, provides concrete examples throughout. Readers gain imperative direction for collaborative, algorithmic, and autonomous writing futures.
Understanding Language Understanding
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Author : Ashwin Ram
language : en
Publisher: MIT Press
Release Date : 1999
Understanding Language Understanding written by Ashwin Ram and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Language Arts & Disciplines categories.
This book highlights cutting-edge research relevant to the building of a computational model of reading comprehension, as in the processing and understanding of a natural language text or story. The book takes an interdisciplinary approach to the study of reading, with contributions from computer science, psychology, and philosophy. Contributors cover the theoretical and psychological foundations of the research in discussions of what it means to understand a text, how one builds a computational model, and related issues in knowledge representation and reasoning. The book also addresses some of the broader issues that a natural language system must deal with, such as reading in context, linguistic novelty, and information extraction.