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Ashutosh Vashisht

Ashutosh Vashisht

B.Tech (IT) Student at Amity School of Engineering and Technology

South West Delhi, Delhi, India •
11 posts •
Machine Learning (ML)

BERT for text summarization

BERT (Bidirectional tranformer) is a transformer used to overcome the limitations of RNN and other neural networks as Long term dependencies. We have explored in depth how to perform text summarization using BERT.

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

Text Summarization using RNN

Encoder Decoder RNN (Recurrent neural network) model is used in order to overcome all the limits faced by the NLP for text summarization such as getting a short and accurate summary.

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

PageRank

PageRank is an algorithm to assign weights to nodes on a graph based on the graph structure and is largely used in Google Search Engine being developed by Larry Page

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

LexRank method for Text Summarization

LexRank method for text summarization is another child method to PageRank method similar to TextRank. It uses a graph based approach for text summarization

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

Graph based approach for Text summarization (Reduction)

In this article we will understand Graph based approach for text summarization (also known as Graph Reduction). It uses techniques to reducing graph size such as predicate-argument mapping and normalization.

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

Edmundson Heuristic Method for text summarization

Edmundson Heuristic Method proposes the use of a subjectively weighted combination of features as opposed to traditionally used feature weights generated using a corpus

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

Luhn’s Heuristic Method for text summarization

The idea of Luhn’s Heuristic Method for text summarization is that any sentence with maximum occurrences of the highest frequency words(Stopwords) and least occurrences are not important to the meaning of the document

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

KL Sum algorithm for text summarization

Kullback-Lieber (KL) Sum algorithm for text summarization which focuses on minimization of summary vocabulary by checking the divergence from the input vocabulary.

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

Latent Semantic Analysis for text summarization

Latent Semantic Analysis is an efficient technique for text summarization in order to abstract out the hidden context of the document.

Ashutosh Vashisht Ashutosh Vashisht
Machine Learning (ML)

SumBasic algorithm for text summarization

SumBasic is an algorithm to generate multi-document text summaries. Basic idea is to utilize frequently occuring words in a document than the less frequent words so as to generate a summary

Ashutosh Vashisht Ashutosh Vashisht
Software Engineering

Abstract Base class in Python

In this article we will discuss about Abstract base classes in Python. Abstract classes are an implementation of Abstraction in Object Oriented approach.

Ashutosh Vashisht Ashutosh Vashisht
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