Sentiment analysis (also known as opinion mining ) refers to the use of natural language processing, text analysis, computational linguistics to systematically identify, extract, quantify, and study affective states and subjective information. [1] In short, Sentiment analysis gives an objective idea of whether the text uses mostly positive, negative, or neutral language. [2] Sentiment analysis … Read more
Whoosh is a python library of classes and functions for indexing text and then searching the index. If the application requires text documents search functionality, Whoosh module can be used for this task. This post will summarize main steps needed for implementing search with Whoosh. Using Whoosh consists of indexing documents and then querying (searching) … Read more
Chatbots are now used in many applications for different purposes. The popularity of this type widget can be estimated from this fact: As of August 2019, search results on Google for the following keywords: chatbot – Volume: 246,000 searches per month and found 32,700,000 results neural net – Volume 3600 searches per month and 127,000,000 … Read more
Extracting data from the Web using scripts (web scraping) is widely used today for numerous purposes. One of the parts of this process is downloading actual text from urls. This will be the topic of this post. We will consider how it can be done using the following case examples: Extracting information from visited links … Read more
In this post (and few following posts) we will look how to get interesting information by extracting links from results of Twitter search by keywords and using machine learning text mining. While there many other posts on the same topic, we will cover also additional small steps that are needed to process data. This includes … Read more
In this post we will look at using ELMo for computing similarity between text documents. Elmo is one of the word embeddings techniques that are widely used now. In the previous post we used TF-IDF for calculating text documents similarity. TF-IDF is based on word frequency counting. Both techniques can be used for converting text … Read more
Despite of the appearance of new word embedding techniques for converting textual data into numbers, TF-IDF still often can be found in many articles or blog posts for information retrieval, user modeling, text classification algorithms, text analytics (extracting top terms for example) and other text mining techniques. In this text we will look what is … Read more
With advance of machine learning , natural language processing and increasing available information on the web, the use of text data in machine learning algorithms is growing. The important step in using text data is preprocessing original raw text data. The data preparation steps may include the following: Tokenization Removing punctuation Removing stop words Stemming … Read more
In the previous post How to Create a Chatbot with ChatBot Open Source and Deploy It on the Web I wrote how to deploy ChatterBot on pythonanywhere hosting site with Django webfamework. In this post we will look at few useful chatbots examples for implementing logic in our chatbot. This chatbot was developed in the … Read more
Chatbots have become very popular due to progress in AI, ML and NLP. They are now used on many websites. With increased popularity of chatbots there are many different frameworks to create chatbot. We will explore one of such framework in this post. We will review how to create a chatbot and deploy online based … Read more