Natural Language Processing

NLP - Word Level Analysis

NLP - Word Level Analysis

The language used to specify text search strings is called a regular expression (RE). Using a unique syntax that is stored in a pattern, RE aids us in matching or finding other strings or sets of strings. Both in UNIX and MS Word, regular expressions are used similarly to search text.

  • Finite State Automata: The plural form of the word automaton is automata, and an automaton is an abstract self-propelled computing device that automatically performs a predetermined sequence of operations.
  • Morphological Parsing: The challenge of realizing that a word can be broken down into linguistic structures known as morphemes, or smaller meaningful units, is known as morphological parsing. 

Types of Morphemes: The two types of morphemes, the smallest units with meaning, are

  • Stems: It is a core meaningful unit of a word.
  • Word order: Morphological parsing would determine the word order. criteria for developing a morphological parser:
    • Lexicon: The first requirement for creating a morphological parser is a lexicon, which contains a list of stems and affixes as well as some basic details about each one. For example, whether the stem is a Noun stem or a Verb stem, and so on.
    • Morphotactics: It is essentially the morpheme ordering model. In other words, the model explains which morpheme classes can follow which morpheme classes within a word.
    • Orthographic rules: The changes that take place in a word are modeled using these spelling rules.

Top course recommendations for you

    AI in Healthcare
    2 hrs
    Beginner
    18.2K+ Learners
    4.59  (1413)
    Machine Translation
    2 hrs
    Intermediate
    3.9K+ Learners
    4.52  (563)
    Introduction to Neural Networks and Deep Learning
    3 hrs
    Intermediate
    64.5K+ Learners
    4.57  (2212)
    Computer Vision Projects
    2 hrs
    Intermediate
    8.2K+ Learners
    4.5  (266)
    TensorFlow Python
    3 hrs
    Intermediate
    9.6K+ Learners
    4.49  (528)
    OpenCV Tutorial
    2 hrs
    Beginner
    5.9K+ Learners
    4.48  (336)
    NLP Customer Experience
    1 hrs
    Intermediate
    3.6K+ Learners
    4.51  (223)
    CNN Process
    1 hrs
    Intermediate
    1.1K+ Learners
    4.41  (41)