1. What Is Nlp?
Answer: Natural Language Processing or NLP is an automated way to understand or analyze the natural languages and extract required information from such data by applying machine learning Algorithms.
2. List Some Components Of Nlp?
Answer: Below are the few major components of NLP.
a. Entity extraction:
It involves segmenting a sentence to identify and extract entities, such as a person (real or fictional), organization, geographies, events, etc.
b. Syntactic analysis:
It refers to the proper ordering of words.
c. Pragmatic analysis:
It is a part of the process of extracting information from text.
3. List Some Areas Of Nlp?
Answer: Natural Language Processing can be used for
1. Semantic Analysis
2. Automatic summarization
3. Text classification
4. Question Answering
4. Define The Nlp Terminology?
Answer: NLP Terminology is based on the following factors:
a. Weights and Vectors:
TF-IDF, length(TF-IDF, doc), Word Vectors, Google Word Vectors
b. Text Structure:
Part-Of-Speech Tagging, Head of sentence, Named entities
c. Sentiment Analysis:
Sentiment Dictionary, Sentiment Entities, Sentiment Features
d. Text Classification:
It is a Supervised Learning, Train Set, Dev(=Validation) Set, Test Set, Text Features, LDA.
e. Machine Reading:
Entity Extraction, Entity Linking,dbpedia, FRED (lib) / Pikes.
5. What Is The Significance Of Tf-idf?
Answer: Tf–idf or TF IDF stands for term frequency–inverse document frequency. Information retrieval TF IDF is a numerical statistic that is intended to reflect how important a word is to a document in a collection or in the collection of a set.