At the end of March, the German government sponsored a hackathon called #WirVsVirus. The aim was to bring Germany’s collective coding expertise to bear on some of the many problems surrounding COVID-19. In total, more than 27,000 coders joined the challenge, working from home, and programming for 48 hours from
Natural Language Processing can offer invaluable benefits to councils and increase resident satisfaction.
A major UK insurance company used text analytics to categorise complaints.
Analyzing tweets is challenging because of their succinctness (max 280 characters). However, that task is facilitated by the powerful features of SAS Visual Text Analytics (VTA), which includes embedded machine learning algorithms.
Which measures financial services can take to keep their customers complaints at a minimum.
Generating a word cloud (also known as a tag cloud) is a good way to mine internet text. Word (or tag) clouds visually represent the occurrence of keywords found in internet data such as Twitter feeds.
If you consume NBA content through social media, then you know just how active that online community is. Basketball arguments and ‘hot takes’ on the Internet are about as commonplace as Michael Jordan playing golf instead of running a functional NBA front office. I wondered if NBA fans happened to
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
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
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
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,
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
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?
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.
In my first post I looked at the role of analytics in policing and how analytics could and should be used to benefit modern policing. However, a key point that can be forgotten is analytics is only as good as the data it is based on. It’s vital to have
As someone who worked in the police force for many years, I know just how important each small piece of evidence can be in securing a conviction. So in times of tightening budgets, imagine how useful it could be to have technology that helps predict when or where crimes will
É um dos flagelos do século - o tráfico humano. Seja de crianças para trabalho inapropriado, seja de mulheres para a prostituição. É algo que ocorre por todo o mundo, com movimentações levadas a cabo por grupos bem organizados e que movimenta muitos milhões de euros. Tom Sabo, Principal Solutions
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
This is the first article in a three-part series on how to reduce uncertainty in the supply chain for lower costs. This article deals with reducing uncertainty downstream – i.e., in relations with customers (and their customers). There are several ways to define uncertainty. I like two angles, which are
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
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
Não poucas vezes sou confrontado com pessoas que me questionam da necessidade de utilização de uma plataforma de advanced analytics para resolver temas como interpretação de texto ou risco de crédito. A pergunta tem o seu quê de racional porque, na verdade, os algoritmos de aprendizagem mecânica não evoluíram assim
It is estimated that that many companies now hold over 80% of their data in an unstructured form. In other words, not as numbers or code, but free text. This textual data arises from social media, customer comments, call center notes, books, emails, messages and the like, and holds enormous
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
The government has an unfathomable amount of data -- and it grows more and more each year. This puts agencies in a unique and important position to use that data for good. Whether it be improving government operations, solving some of the nation’s biggest challenges or empowering citizens in new
To demonstrate the power of text mining and the insights it can uncover, I used SAS Text Mining technologies to extract the underlying key topics of the children's classic Alice in Wonderland. I want to show you what Alice in Wonderland can tell us about both human intelligence and artificial
Recently I backed into a hotel parking spot after returning from a customer dinner. It was dark and rainy, and I was tired from traveling. My mind wandered until I heard a shrill “BEEP BEEP BEEP” coming from my rental car. I looked down at the dashboard’s rear-view camera, and
The Obama administration made great strides in improving the government’s use of information technology over the past eight years, and now it's up to the Trump administration to expand upon it. Let’s look at five possible Trump administration initiatives that can take government’s use of information technology to the next
Each day, the SAS Customer Contact Center participates in hundreds of interactions with customers, prospective customers, educators, students and the media. While the team responds to inbound calls, web forms, social media requests and emails, the live-chat sessions that occur on the corporate website make up the majority of these
Mal ehrlich, wenn ich Sie fragen würde, worüber die Kandidaten im diesjährigen US-Wahlkampf in ihren Aufeinandertreffen debattiert haben – welche Kernthemen würden Sie mir spontan (abseits von Skandalen und Affären) nennen? Und könnten Sie diese Kernthemen den einzelnen Kandidaten zuordnen? Als ich mir diese Frage stellte, war die Antwort –
