
Annamalai Natural Language Processing SemVIIIElective Unit 1 : Introduction(Speech and Language Processing  Ambiguity  Models and algorithms  Language  Thought  Understanding  Brief history  Regular Expressions  Automata  Morphology and Finite State Transducers  Computational Phonology
and TexttoSpeech) 


1. Cognitive Psychology(Psychology) 
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Cognitive Psychology separates itself from philosophy by depending on experiments that measure. They are interested in the internal processes taking place within the individual.Experimental studies are the heart of cognitive psychology. Unfortunately there is no way to literally watch a person think. We must rely on external indicators, such as how well or how
quickly a person can perform a certa
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Title: MPSY11 Systems and Contemporary Trends in Psychology




2. Introduction to Finite Automata(Formal Languages and Automata Theory
) 
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This chapter contains topics such as: Central concepts of Automata theory, Deterministic Finite Automata, Nondeterministic Finite Automata with numerous examples
Title: Finite Automata and Formal Languages




3. Chapter 1 * Introduction to Bioinformatics(Biotechnology) 
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Title: Bioinformatics
Published on: 03/04/20
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Pages:
54








4. Introduction to Finite Automata and DFA(Computer Science) 
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A Finite State Machine (FSM) is a model of behavior using states and state
transitions. A transition is a state change triggered by an input event, i.e. transitions map some stateevent pairs to other states. As indicated in the name, the set of states should be finite. Also, it is assumed that there is a finite set of distinct input events or their categories (types, classes). Subsequently, the
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Title: MSCS516C Theory of Computation




5. Introduction to Algorithm(Analysis and Design of Algorithms (ADA)) 
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◙ What's an Algorithm, ◙ Solving a Problem, ◙ Understanding the Problem, ◙ Understanding the Computational Means,
◙ Choosing Appropriate Data Structure, ◙ Precision of Solution, ◙ Strategy to Conquer the Problem, ◙ Representing the Algorithm, ◙ Testing and Analyzing the Algorithm,
◙ Implementing the Algorithm, `
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Title: Introduction to ADA




6. Finite Automata and Conversion from NFA to DFA(Computer Science) 
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The extension to NFA  a "feature" called epsilon transitions, denoted by E, the empty string. The E transition lets us spontaneously take a transition, without receiving an input symbol. This is another mechanism that allows NFA to be in multiple states at once.
Title: MSCS516C Theory of Computation





7. Dewey Decimal Classification (Edition 21): An Overview(Library and Information Science) 
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In practice book classification essentially includes analysing the subject content of a document and arriving at a corresponding notation, i.e., class number prescribed by the scheme of classification of books according to Dewey Decimal Classification (Edition 21) or simply DDC 21.This Unit, in particular gives an overall structure and salient features of DDC 21.
Title: BLI57 Information Processing Practical (Classification)




8. Undecidability(Formal Languages & Automata Theory) 
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While the thesis which equates an intuitive concept and a precise formal model cannot be proved, there is enough evidence to support the thesis. Hereafter, we use the term 'effective procedure'and 'Turing machine' synonymously. A problem is solvable if there is a procedure (Turing machine) to solve it. Now, the question is: is every problem solvable? To answer this philosophical problem, we have t
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Title: Formal Languages & Automata Theory




9. Undecidability(Formal Languages and Automata Theory
) 
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This chapter includes topics such as: A Language that is not recursively enumerable, An Undecidable problem that is RE, Post's Correspondence problem, Other undecidable problems.
Title: Finite Automata and Formal Languages




10. Regular Languages & Properties of Regular Languages(Formal Languages and Automata Theory
) 
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This chapter includes various topics such as: Regular languages, Proving languages not to be regular languages, Closure properties of regular languages, Decision properties of regular languages, Equivalence and minimization of automata
Title: Finite Automata and Formal Languages




11. NonDeterministic Finite Automata and Applications(Computer Science) 
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An interesting connection lies between the ideas of Nondeterminism and the theory of finite automata, which is part of the theory of computation. Earlier, it was mentioned that determining whether there exists some string that is accepted by a DFA is equivalent to a discrete feasible planning problem. In addition, in real time environment, there may be some complex.situations where it is very dif
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Title: MSCS516C Theory of Computation




12. Regular Expressions and Regular Languages(Formal Languages & Automata Theory) 
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A regular expression is another medium for concise and precise specification of languages. Regular expressions were studied extensively by S.C. Kleene. It turns out that regular expressions specify the same class of languages which can be recognized by FA. This equivalence has made regular expression a convenient input language in lexical analyzer generators (LEX) and many text formatting packages
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Title: Formal Languages & Automata Theory




13. Introduction(Formal Languages & Automata Theory) 
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Ever since the advent of civilisation, man has shown interest in creating machines to replace/ease human labour. Hence, it is not surprising that he felt the need for a machine that would do laborious computation for him. In 16th century, Pascal invented a rudimentary computing device. In 19th century, Charles Babbage actually built a machine called analytical engine which had the essential charac
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Title: Formal Languages & Automata Theory




14. Computational Algorithms for the Configuration Design (Aerodynamics Airworthiness)(Aeronautical Engineering) 
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Introduction, Theoretical Algorithms, Computational Algorithms, Optimization of Computational Grids , Parallel Computational Computing.
Title: Aerodynamics Airworthiness




15. Computational Algorithms for the Configuration Design (Aerodynamics Airworthiness)(Aeronautical Engineering) 
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• Introduction
• Theoretical Algorithms
• Computational Algorithms, Optimization of Computational Grids
• Parallel Computational Computing
Title: Aerodynamics Airworthiness





16. INTRODUCTION(Computer Science) 
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An Algorithm is any welldefined computational procedure that takes some value or set of values as input and produces a set of values or some value as output. Thus algorithm is a sequence of computational steps that transforms the input into the output.
Title: DESIGN AND ANALYSIS OF ALGORITHMS
Published on: 01/10/18
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17. Additional TopicsA Bird's Eye View(Formal Languages & Automata Theory) 
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Equivalence between Turing Machines and Type0 languages: For every TM M, we can construct an equivalent grammar G and viceversa. Equivalence between Context Sensitive Languages and Linear Bounded Automata: Linear Bounded Automata is a nondeterministic TM which does not use any tape space beyond input limits. For every CSG G, there is an equivalent LBAM and viceversa. A brief outline of space co
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Title: Formal Languages & Automata Theory




18. Module 1(Computer Science) 
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Introduction:
What is an Algorithm? (T2:1.1), Algorithm Specification (T2:1.2), Analysis Framework (T1:2.1), Performance Analysis: Space complexity, Time complexity (T2:1.3).
Asymptotic Notations:
BigOh notation (O), Omega notation (Ω), Theta notation (Θ), and Littleoh notation (o), Mathematical analysis of NonRecursive and recursive Algorithms with Examples (T1:2.2, 2.3, 2.4).
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Title: Design and Analysis of Algorithms
Published on: 12/05/20
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44








19. Finite Automata(Formal Languages & Automata Theory) 
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Finite automata is the simplest of different classes of automata. It has 3 variations − Deterministic finite automata (DFA), Non deterministic finite automata (NFA) and NFA with ∈ − moves. In DFA, at each step, next move is uniquely determined. In NFA, at any stage, it is given a choice from a predefined set of moves. In ∈NFA, automaton is capable of change of state withou
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Title: Formal Languages & Automata Theory





21. Chapter 14 * System Biology(Biotechnology) 
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Title: Bioinformatics
Published on: 03/04/20
Author:
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Pages:
47








22. Learning An Introduction(B.Ed General) 
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After studying this Unit you will be able to: Define the concept of Learning. Explain the nature of Learning. Define the concepts of Development and Maturation. Bring out the relationship between Learning, Development, and Maturation. Justify the need for a 'school'. Explain Learning as Information Processing.
Title: BEd CC02 Understanding the Learner and Learning Process




23. Properties of Regular Languages(Formal Languages & Automata Theory) 
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In this chapter, we discuss various properties of languages recognized by Finite Automata. We try to answer many questions that can be asked about the regular languages. Is a given regular language empty? finite? infinite? What are the limitations of regular languages? Also, we discuss the closure properties of regular languages under various operations.
Title: Formal Languages & Automata Theory




24. Methods of Psychology Part 1(Psychology) 
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A theory is a wellestablished principle that has been developed to explain some aspect of the natural world. A theory arises from repeated observation and testing and incorporates facts, laws, predictions, and tested hypotheses that are widely accepted. A hypothesis is a specific, testable prediction about what we expect to happen in our study. For example, a study designed to look at the relatio
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Title: BPY 11 Basic Psychological Processes




25. Unit01(Compiler Design) 
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Introduction, Lexical analysis: Language processors; The structure of a Compiler; The evolution of programming languages; The science of building a Compiler; Applications of compiler technology; Programming language basics. Lexical analysis: The Role of Lexical Analyzer; Input Buffering; Specifications of Tokens; Recognition of Tokens
Title: COMPILER DESIGN/10CS63






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