Tag: natural language processing

Artificial Intelligence | Cloud | Innovation | Internet of Things | Predictions
Spiros Potamitis 0
Getting a glimpse into the future of forecasting

In a global economy marked by fragile supply chains, scarce resources and rising energy costs, the spotlight is on forecasting to address these issues. In 2022, McKinsey & Company uncovered a staggering $600 billion annual food waste, equating to 33% – 40% of global food production, spotlighting the devastating consequences

Advanced Analytics | Data for Good | Machine Learning
Cristina Pérez 0
Analítica de textos e IA para identificar patrones de trata de seres humanos en la documentación policial

La información que los organismos policiales almacenan sobre detenciones o incidentes delictivos, así como los avisos a los departamentos de policía, tienen un valor enorme para resolver futuros casos que se pueden plantear. Analizar manualmente esta gran cantidad de datos en busca de patrones puede llevar mucho tiempo y sus

Vrushali Sawant 0
The ethics of responsible innovation: Why transparency is key

In today's world, data-driven systems make significant decisions across industries. While these systems can bring many benefits, they can also foster distrust by obscuring how decisions are made. Therefore, transparency within data driven systems is critical to responsible innovation. Transparency requires clear, explainable communication. Since transparency helps people understand how

Advanced Analytics | Data Management | Fraud & Security Intelligence
Colin Field 0
Law enforcement needs text analytics on the case to overcome massive data analysis challenge

Imagine trying to dig a useful bit of information out of 50,000 lines of a chat log? Now, imagine if that needle in the haystack was the difference in a criminal being arrested or staying at-large? Thousands of lines of confusing and unreadable chat text are more and more frequently

Advanced Analytics | Analytics | Data Management
Estelle Wang 0
Find duplicates and near-duplicates in a corpus with Natural Language Processing

To find exact duplicates, matching all string pairs is the simplest approach, but it is not a very efficient or sufficient technique. Using the MD5 or SHA-1 hash algorithms can get us a correct outcome with a faster speed, yet near-duplicates would still not be on the radar. Text similarity is useful for finding files that look alike. There are various approaches to this and each of them has its own way to define documents that are considered duplicates. Furthermore, the definition of duplicate documents has implications for the type of processing and the results produced. Below are some of the options. Using SAS Visual Text Analytics, you can customize and accomplish this task during your corpus analysis journey either with Python SWAT package or with PROC SQL in SAS.

Analytics | Artificial Intelligence | Data Management
Marinela Profi 0
The social impact of data science: improving the mental health for cancer patients with AI

A cancer journey affects both physical and mental health. This often results in feelings of social isolation, loss of identity, clinical depression and even PTSD. This often goes unrecognized and undiagnosed due in part to lack of resources, tools and time. Swedish startup War On Cancer wondered whether they could

Advanced Analytics | Data Visualization | Machine Learning
Falko Schulz 0
Analyzing movement and tracking data using SAS Visual Analytics

Technological advancements in connectivity and global positioning systems (GPS) have led to increased data tracking and related business use cases to analyze such movements. Whether analyzing a vehicle, an animal or a population's movements - each use case requires analyzing underlying spatial information. Global challenges such as virus outbreaks, deforestation

Machine Learning
Katie Tedrow 0
Enhancing your Natural Language Processing: Intro to Conversational AI

Conversational AI can offer a way to provide that always-on 24/7, fast, convenient experience that can go anywhere (phone, computer smart speakers, even your car). It can provide a human-like experience through real-time, personalized interaction with AI running in the background. This technology is being applied across many industries for a variety of use cases (both customer-facing and for internal use).

Machine Learning
Katie Tedrow 0
The hybrid approach to enhancing your natural language processing

Unlocking the potential of your unstructured text data can lead to great business outcomes but the prospect of starting a new or enhancing your existing Natural Language Processing (NLP) program can feel overwhelming because of the inherently unique (and sometimes messy) nature of human language. Text data doesn’t fit neatly into rows or columns the way that structured data does, which can make it seem more complex to work with. Conversations and written language range from objective statements to subjective perspectives and opinions. The same sentence, depending on its intent and the nuances in how it's said, can have a positive, negative, or neutral sentiment. To get us started, we'll share different types of NLP models used to analyze unstructured data with a focus on the hybrid approach.

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