How rapid analytics app deployment accelerates transformation
I think that this pandemic has put digital transformation at the top of every executive agenda.
Tag: natural language processing
Natural language processing in local government
Natural Language Processing can offer invaluable benefits to councils and increase resident satisfaction.
'Please hold, your call is important to us'
Which measures financial services can take to keep their customers complaints at a minimum.
What can we learn from Clippy about AI?
Interestingly enough, paperclips have their own day of honor. On May 29th we celebrate #NationalPaperclipDay! That well-known piece of curved wire deserves attention for keeping our papers together and helping us stay organized. Do you remember who else deserved the same attention? Clippit – the infamous Microsoft Office assistant, popularly known as ‘Clippy’.
Can we evaluate whole person suffering?
As we honor Mental Health Month, there are many calls to reduce suffering. Seems reasonable, right? It’s even in California’s Mental Health Services Act (MHSA), where public systems are called to “reduce subjective suffering.” And as we broadly focus more on outcomes in health, measuring suffering (and hopefully its reduction)
Analysis of Movie Reviews using Visual Text Analytics
This blog shows how the automatically generated concepts and categories in Visual Text Analytics (VTA) can be refined using LITI and Boolean rules. I will use a data set that contains information on 1527 randomly selected movies: their titles, reviews, MPAA Ratings, Main Genre classifications and Viewer Ratings.
Sentiment Analysis using DeepRNN Action Set
In this blog, I use a Recurrent Neural Network (RNN) to predict whether opinions for a given review will be positive or negative. This prediction is treated as a text classification example. The Sentiment Classification Model is trained using deepRNN algorithms and the resulting model is used to predict if new reviews are positive or negative.
Moving from natural language processing to natural language understanding
Imagine a world where satisfying human-computer dialogues exist. With the resurgence of interest in natural language processing (NLP) and understanding (NLU) – that day may not be far off. In order to provide more satisfying interactions with machines, researchers are designing smart systems that use artificial intelligence (AI) to develop
Les Bots : nouvelle vague de la 4ème révolution industrielle
Et si, en dehors de la nouvelle organisation des moyens de production, la 4ème révolution industrielle induisait également une évolution significative dans la gestion de la connaissance intrinsèque à chaque domaine ? Et si les nouvelles technologies numériques permettaient aux acteurs opérationnels d’accéder simplement à cette connaissance, le plus souvent fruit de méthodes
So, you’ve figured out NLP but what’s NLU?
Natural language understanding (NLU) is a subfield of natural language processing (NLP) that enables machine reading comprehension. While both understand human language, NLU goes beyond the structural understanding of language to interpret intent, resolve context and word ambiguity, and even generate human language on its own. NLU is designed for
Countering human trafficking using text analytics and AI
Recently, the North Carolina Human Trafficking Commission hosted a regional symposium to help strengthen North Carolina’s multidisciplinary response to human trafficking. One of the speakers shared an anecdote from a busy young woman with kids. She had returned home from work and was preparing for dinner; her young son wanted
Text analytics explained
Structuring a highly unstructured data source Human language is astoundingly complex and diverse. We express ourselves in infinite ways. It can be very difficult to model and extract meaning from both written and spoken language. Usually the most meaningful analysis uses a number of techniques. While supervised and unsupervised learning,
SAS deep learning with Python made easy using DLPy
I look forward to Pi Day every year at SAS because it's a day of celebration including yummy pies and challenging games that challenge you to recall the digits after the decimal point in Pi. Plus you get to wear Pi t-shirts (I have about seven). Today, though we are going to talk about DLPy which sounds like Pi and
5 ways analytics is used at the Special Olympics
The Special Olympics is part of the inclusion movement for people with intellectual disabilities. The organisation provides year-round sports training and competitions for adults and children with intellectual disabilities. In March 2019 the Special Olympics World Games will be held in Abu Dhabi, United Arab Emirates. SAS is an official
Automatically extracting key information from textual data
There is tremendous value buried text sources such as call center and chat dialogues, survey comments, product reviews, technical notes, legal contracts... How can we extract the signal we want amidst all the noise?
Practical approaches to new product forecasting using structured and unstructured data
When it comes to forecasting new product launches, executives say that it's a frustrating, almost futile, effort. The reason? Minimal data, limited analytic capabilities and a general uncertainty surrounding a new product launch. Not to mention the ever-changing marketplace. Nevertheless, companies cannot disregard the need for a new product forecast
NLP for military intelligence
Every day, military intelligence analysts sit behind computers reading a never-ending stream of reports, updating presentation templates and writing assessments. But intelligence is more than documenting events and sharing breaking news. It involves understanding and predicting complexities in human behavior across various organizational constructs and using facets of information to
Convert a text-based measurement to a number in SAS
Regular expressions are a powerful method for finding specific patterns in text. The syntax of regular expressions is intimidating, but once you've solved a few pattern-recognition problems with regex, you'll never go back to your old methods.
Reduce the cost-barrier of generating labeled text data for machine learning algorithms
Amidst the growing popularity of modern machine learning and deep learning techniques, one of the biggest challenges is the ability to obtain large amounts of training data suitable for your use case. This post discusses how the analytical approach for Named Entity Recognition (NER) can help.
Why you need GPUs for your deep learning platform
Deep learning has taken off because organizations of all sizes are capturing a greater variety of data and can mine bigger data, including unstructured data. It’s not just large companies like Amazon, SAS and Google that have access to big data. It’s everywhere. Deep learning needs big data, and now
How to calculate Word Mover's Distance with SAS
Word Mover's Distance (WMD) is a distance metric used to measure the dissimilarity between two documents, and its application in text analytics was introduced by a research group from Washington University in 2015. The group's paper, From Word Embeddings To Document Distances, was published on the 32nd International Conference on Machine
Shining a spotlight on human trafficking
My local middle school publishes a weekly paper. Very recently, I noted an article in that paper regarding an expose on human trafficking overseas, "World Slavery: The Terrors Our World Tries to Forget." The eloquent article in part highlighted how children have been exploited in the fishing industry in Ghana
5 remarkable uses for text analytics
Maybe you’ve heard of text analytics (or natural language processing) as a way to analyze consumer sentiment. Businesses often use these techniques to analyze customer complaints or comments on social media, to identify when a response is needed. But text analytics has far more to offer than examining posts on
13 Ways to Use AI in Military Intelligence
As a former intelligence analyst, I can't help but breathe a huge sigh of frustration. The special AI "task forces" and their massive budgets are great, but it's time to get honest about the rest of the military. Ask any every day soldier, sailor, airman or Marine their opinion of
Let's chat about chatbots
A chatbot is a computer program that uses natural language processing (NLP) and artificial intelligence to simulate human conversation and derive a response. Essentially, it’s a machine that can chat with you or respond to your chatter. Chatbots can save time and money when used to handle simple, automated tasks.
Could text analytics be the cutting-edge technology the oil and gas industry was waiting for?
Small causes can have large effects; or how a discovery in the Barnett Shale can spike some interest in the rest of the world and change the face of the industry. This article is co-written by Sylvie Jacquet-Faucillon, Senior Analytics Presales Consultant, SAS France; and David Dozoul, Senior Adviser
SAS® Text Analytics and Text Mining in Action: Experiences From a ‘Self-Trial’ With SAS® Contextual Analysis
Don’t get me wrong. I have no doubt in the capabilities of our SAS products and SAS solutions! But I wanted to get a firsthand experience of our new solution for text analytics, SAS Contextual Analysis 14.1. And the result is very convincing! But let’s start from the beginning. Functions
Voice of the customer analysis (Part 1)
This is the first of two articles looking at how to listen to what your customers are saying and act upon it – that is, how to understand the voice of the customer. Over the last few years, one of the big uses for SAS® Text Analytics has been to
Cognitive Computing - Part 1
Is cognitive computing an application of text mining? If you have asked this question, you are not alone. In fact, lately I have heard it quite often. So what is cognitive computing, really? A cognitive computing system, as stated by Dr. John E. Kelly III, is one that has the
To data scientists and beyond! One of many applications of text analytics
Hi, there! First of all, let me introduce myself, as this is my first blog. I am Simran Bagga, and three weeks ago I became the Product Manager for Text Analytics at SAS. This role might be new to me, but text analytics is not. For the past 12 years,