Basics

Natural Language Processing: Natural Language Processing, NLP for short, is the subfield of linguistics, computer science, and artificial intelligence, that concerns with the automated translation of Human Language, for computers to process and analyze large amounts of natural language data

Data Preprocessing: Data preprocessing is a process of preparing the raw data and making it suitable for a machine learning model

Tokenization: An important step in textual data preprocessing, tokenization is transformation of larger chunk of string, into smaller chunks, i.e. tokens

Sentimental: Having or arousing feelings ^def

Stop Words: Those words which are eliminated from the data, which contribute little to overall determination of sentimental-value, as known as Stop Word. E.g. And, Because, Very, The, An, etc.

Morphmeme: In linguistic study of language, a Morpheme is A morpheme is the smallest part of a word that has grammatical function or meaning, e.g. Credits: colostate.edu

Free Morpheme: A Morpheme which can which can stand alone as meaniungful word, is called as Free Morpheme, e.g.

Root Word: A root is the simplest form attainable by separating a word into its component parts

Stem: The body of a word, to which the "terminations" are attached, is called the stem

Stemming: Stemming is the process of eliminating affixes (suffixed, prefixes, infixes, circumfixes) from a word in order to obtain a word stem

Lemma: Lemma is base or dictionary form of a word

Lemmatization: Lemmatization is related to stemming, differing in that lemmatization is able to capture canonical forms based on a word's lemma
e.g. words like break, breaks, broke, broken and breaking are all originated from the same source (lexeme), i.e. "break". And "break" is thier lemma, by which they are all indexed Credits: nlp.stanford.edu

Corpus: A collection of texts is called as Corpus (plural: Corpora)