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Naushad UzZaman's Projects

streaming_lsh icon streaming_lsh

A project for clustering text streams using locality-sensitive hashing (LSH) in Python

symspell icon symspell

SymSpell: 1 million times faster through Symmetric Delete spelling correction algorithm

tempeval3_toolkit icon tempeval3_toolkit

Evaluation toolkit for evaluating temporal information. Evaluated TempEval-3 participants using this script.

tensorflow_fasttext icon tensorflow_fasttext

Simple embedding based text classifier inspired by fastText, implemented in tensorflow

text_simplification icon text_simplification

Text Simplification Model based on Encoder-Decoder (includes Transformer and Seq2Seq) model.

textblob icon textblob

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

textstat icon textstat

:memo: python package to calculate readability statistics of a text object - paragraphs, sentences, articles.

thechainranker icon thechainranker

Automated text summarization system using Lexical chains and Lex Rank

topic-modelling-on-wiki-corpus icon topic-modelling-on-wiki-corpus

It uses Latent Dirichlet Allocation algorithm to discover hidden topics from the articles. It is trained on 60,000 articles taken from simple wikipedia english corpus. Finally, It can extract the topic of the given input text article.

trump-twitter-classify icon trump-twitter-classify

Uses a Naive Bayes classifier to detect whether Trump has authored a given @RealDonaldTrump tweet.

twarc icon twarc

A command line tool (and Python library) for archiving Twitter JSON

twick icon twick

Twitter, quick. Fetch and store tweets on short notice.

twint icon twint

An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations.

twitter-trends-summarizer icon twitter-trends-summarizer

NLP: An Approach to Automatic Trending Tweet Summarization. Summaries will greatly help the user in understanding β€œwhy the topic is trending”. We have proposed an algorithm which automatically generates summaries for trending topics/hashtags based on tweets and it's related news article.

twitterner icon twitterner

Twitter named entity extraction for WNUT 2016 http://noisy-text.github.io/2016/ner-shared-task.html

urlcheck icon urlcheck

Malicious Web Sites Detection using Suspicious URL

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