NLP Top Exam Questions and answers. 100% Accurate. Verified.

NLP Top Exam Questions and answers. 100% Accurate. Verified. Natural Language Processing (NLP) - -Increases availability of text Technical: UI, information retrieval, extraction Domain: Business-Google Advertising, Comp Sci: voice recognition Tools and Resources for NLP - -Like using Python NLTK Morphology - -Single words: made up of morphemes: stems + affixes Example test -> tests, testing Morpheme - -smallest meaning bearing unit Tokenizer - -Recognizes words, root words Playing -> play Sequence of words - -N-gram, useful to build language models for word prediction Syntax - -combining words according to set of rules Basic structure of syntax - -subject - predicate Word classes - -Nouns, verbs Syntatic ambiguity - -Same sequence with different meanings like flying planes can be dangerous Impact of meaning on structure like I washed the shirt with soap (shirt and soap go together) Assigning structure to text - -Step 1: POS Tagging : rule based, stochastic, and transformation-based learning Step 2: CFG - rules on how to combine chunks Parsing - -assigning a structure to a text that fits the rules Semantics - -connecting linguistic elements to non-linguistic knowledge of the world (meaning of words) Pragmatics - -meaning in context, language as a means of communication needs three elements: linguistic expression what expression refers to context Syntax 1 Semantic 1-2 Pragmatic 1-2-3 Word tokens - -number of appearances of distinct words Word types - -number of distnct words Words lemma - -describes the set of lexical forms with the same stem: cats, cat Words NLP - -Text = sequence of characters, recognize the words in the sequence Words tokenizer - -extracts token, rules to split up sequence of characters. Basic: white space Regular Expressions - -formula to describe/specify a string