Normalyzing Numeronyms -- A NLP approach

07/31/2019
by   Avishek Garain, et al.
0

This paper presents a method to apply Natural Language Processing for normalizing numeronyms to make them understandable by humans. We approach the problem through a two-step mechanism. We make use of the state of the art Levenshtein distance of words. We then apply Cosine Similarity for selection of the normalized text and reach greater accuracy in solving the problem. Our approach garners accuracy figures of 71% and 72% for Bengali and English language, respectively.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/10/2019

Un systeme de lemmatisation pour les applications de TALN

This paper presents a method of stemming for the Arabian texts based on ...
research
01/16/2013

A Rhetorical Analysis Approach to Natural Language Processing

The goal of this research was to find a way to extend the capabilities o...
research
02/07/2021

Spoiler Alert: Using Natural Language Processing to Detect Spoilers in Book Reviews

This paper presents an NLP (Natural Language Processing) approach to det...
research
02/21/2022

Embarrassingly Simple Performance Prediction for Abductive Natural Language Inference

The task of abductive natural language inference (αnli), to decide which...
research
05/19/2023

Solving NLP Problems through Human-System Collaboration: A Discussion-based Approach

Humans work together to solve common problems by having discussions, exp...
research
06/27/2020

Normalizador Neural de Datas e Endereços

Documents of any kind present a wide variety of date and address formats...
research
08/28/2016

What to do about non-standard (or non-canonical) language in NLP

Real world data differs radically from the benchmark corpora we use in n...

Please sign up or login with your details

Forgot password? Click here to reset