Dive Into NLTK, Part IX: From Text Classification to Sentiment Analysis

This is the ninth article in the series “Dive Into NLTK“, here is an index of all the articles in the series that have been published to date: Part I: Getting Started with NLTK Part II: Sentence Tokenize and Word … Continue reading →

Deep Learning for NLP resources from Github

Two list of “Deep Learning for NLP resources” from github, just for reference: Deep Learning for NLP resources: Introductory and state of the art resources for NLP sequence modeling tasks like dialog. from https://github.com/andrewt3000/DL4NLP Deep-Learning-for-NLP-Resources: List of resources to get … Continue reading →

Getting Started with Keyword Extraction

Recently, I have surveyed some keyword extraction tools, papers and documents, and record them here for getting started with keyword extraction. According wikipedia, Keyword Extraction is defined like this: Keyword extraction is tasked with the automatic identification of terms that … Continue reading →

Deep Learning for Text Mining from Scratch

Here is a list of courses or materials for you to learn deep learning for text mining from scratch。 Mathematics Everything start from mathematics. 1. Pre-Calculus About the Course Through this course, students will acquire a solid foundation in algebra … Continue reading →

Delete unused demo and update Chinese Word Segmenter Model for Text Analysis Online

We found that the stanford nlp related demo and text summarizer demo affected the text analysis api seriously, so we decided delete the demo from text analysis online, sorry for that. We have update the Chinese Word Segment Model and … Continue reading →

Training Word2Vec Model on English Wikipedia by Gensim

After learning word2vec and glove, a natural way to think about them is training a related model on a larger corpus, and english wikipedia is an ideal choice for this task. After google the related keywords like “word2vec wikipedia”, “gensim … Continue reading →

Getting Started with Word2Vec and GloVe in Python

We have talked about “Getting Started with Word2Vec and GloVe“, and how to use them in a pure python environment? Here we wil tell you how to use word2vec and glove by python. Word2Vec in Python The great topic modeling … Continue reading →

Text Analysis Online no longer provides NLTK Stanford NLP API Interface

Text Analysis Online no longer provides NLTK Stanford NLP API Interface, but keep the related demo just for testing: NLTK Stanford POS Tagger: http://textanalysisonline.com/nltk-stanford-postagger NLTK Stanford Named Entity Recognizer: http://textanalysisonline.com/nltk-stanford-ner NLTK Stanford Named Entity Recognizer for 7Class: http://textanalysisonline.com/nltk-stanford-ner-7class NLTK Stanford … Continue reading →

Getting Started with Word2Vec and GloVe

Word2Vec and GloVe are two popular word embedding algorithms recently which used to construct vector representations for words. And those methods can be used to compute the semantic similarity between words by the mathematically vector representation. The c/c++ tools for … Continue reading →

We have launched the Professional Document Similarity API on Mashape

We have launched the Professional Document Similarity API on Mashape, which support compare two english text document similarity. You can use our demo on the Document Similarity website: Document Similarity Demo. Document Similarity API is based on advanced Natural Language … Continue reading →