The Opinosis Analytics (OA) Blog

How to Hire Help For Your NLP & Machine Learning Projects?
How to Hire Help For Your NLP & Machine Learning Projects?

While big name tech companies have fully staffed Natural Language Processing (NLP) and Machine Learning engineers, your company may be at the cusp of joining the A.I. revolution. At this stage, you ma…

HCAHPS Survey: 10 Frequently Asked Questions
HCAHPS Survey: 10 Frequently Asked Questions

As NLP and Machine Learning consultants, part of what we do is analyze data – primarily text data in combination with structured data to help organizations make informed decisions. However, when it…

How to Streamline Customer Service with NLP?
How to Streamline Customer Service with NLP?

Companies receive support enquiries from various channels. This may include emails, support tickets, tweets, chat conversations with customer support representatives (CSRs), chatbot conversations and …

Leverage Patient Comments to Gain Insights Into Your Practice
Leverage Patient Comments to Gain Insights Into Your Practice

Learn about the different types of insights you can get from detailed analysis of patient comment…

What are N-Grams?
What are N-Grams?

N-Grams are a set of co-occurring words within a given window. When computing n-grams you typical…

What are Stop Words?
What are Stop Words?

Stop words are a set of commonly used words in a language. Examples of stop words in English are …

What is Inverse Document Frequency?
What is Inverse Document Frequency?

Inverse Document Frequency (IDF) is a weight indicating how commonly a word is used. The more fre…

What is Term Frequency?
What is Term Frequency?

Term frequency (TF) often used in Text Mining, NLP and Information Retrieval tells you how freque…

How we use Natural Language Processing for market research?
How we use Natural Language Processing for market research?

In order for companies to innovate, build new product lines and understand the effects of certain…

How we automatically organize large amounts of text data with topics?
How we automatically organize large amounts of text data with topics?

Making sense of volumes of text data in surveys, legal documents, websites, customer support tick…

How we use automatic categorization to make sense of documents?
How we use automatic categorization to make sense of documents?

Enterprises are overwhelmed with the volume of text they have to deal with every day. You have em…

How we surface customer complaints with text mining and analytics?
How we surface customer complaints with text mining and analytics?

Feedback from customers trickles in from different sources including social sources (e.g. Twitter…

NLP Best Practices: Build Production Ready Solutions
NLP Best Practices: Build Production Ready Solutions

A vast majority of NLP solutions developed at the work place just don’t scale! And by scale, we mean handling real world uses cases, ability to handle large amounts of data and ease of deployment in a…