Lexalytics

MAY 25, 2021

One of the most important and most-used functions in text analytics and NLP is sentiment analysis — the process of determining whether a word, phrase, or document is positive, negative, or neutral.

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Unite.AI

FEBRUARY 19, 2024

For example, by leveraging Natural Language Processing (NLP) and text analytics, OCR can proficiently scan and transform handwritten or printed documents, such as prescription labels, patient forms, doctor's notes, and lab results, into digital format.

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SAS Software

MARCH 6, 2023

Editor's note: This article follows Curious about ChatGPT: Exploring the origins of generative AI and natural language processing. As ChatGPT has entered the scene, many fear and uncertainty have been expressed by those working in education at all levels. Educators worry about cheating and rightly so.

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SAS Software

JANUARY 18, 2023

SAS' Kirk Swilley and Tom Sabo showcase how you can use perform text analysis on minimal structured narrative data to spot patterns of possible human trafficking. The post Leveraging text analytics and AI to assess police narrative events indicating human trafficking appeared first on SAS Blogs.

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Analytics Vidhya

JULY 8, 2020

Overview Setting up John Snow labs Spark-NLP on AWS EMR and using the library to perform a simple text categorization of BBC articles. The post Build Text Categorization Model with Spark NLP appeared first on Analytics Vidhya. Introduction.

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Lexalytics

JULY 12, 2023

We’ve pioneered a number of industry firsts, including the first commercial sentiment analysis engine, the first Twitter/microblog-specific text analytics in 2010, the first semantic understanding based on Wikipedia in 2011, and the first unsupervised machine learning model for syntax analysis in 2014.

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AssemblyAI

NOVEMBER 9, 2023

In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. What is Text Summarization for NLP? The models are powered by advanced Deep Learning and Machine Learning research.

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IBM Journey to AI blog

JULY 17, 2023

This allows users to accomplish different Natural Language Processing (NLP) functional tasks and take advantage of IBM vetted pre-trained open-source foundation models. Encoder-decoder and decoder-only large language models are available in the Prompt Lab today. To bridge the tuning gap, watsonx.ai

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IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? This valuable information helps decision-makers refine marketing strategies, improve product offerings and deliver a more personalized customer experience.

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NLP People

DECEMBER 8, 2017

The Unit for Natural Language Processing National University of Ireland, Galway The Insight Centre for Data Analytics, Europe’s largest research centre in data science, has a group in Natural Language Processing (UNLP) at the National University of Ireland Galway.

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NLP People

APRIL 10, 2019

Natural Language Processing has seen some major breakthroughs in the past years; with the rise of Artificial Intelligence, the attempt at teaching machines to master human language is becoming an increasingly popular field in academia and industry all over the world.

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Lexalytics

SEPTEMBER 9, 2021

For nearly two decades, Lexalytics has been a pioneer in structured and unstructured data analytics, translating text into profitable decisions with our natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) solutions for the world’s most customer-centric brands.

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Flipboard

JULY 10, 2023

Unstructured text and data are like gold for business applications and the company bottom line, but where to start? Here are three tools worth a look.

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Marktechpost

JULY 17, 2023

Using causal graphs, LIME, Shapley, and the decision tree surrogate approach, the organization also provides various features to make it easier to develop explainability into predictive analytics models. IBM Watson Studio Since its founding in 1975, SPSS has developed into one of the leading statistical and analytics programs.

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LevelAI

FEBRUARY 5, 2024

Text Analytics: Spotting occurrences of words This approach matches pre-defined keywords or sequences of words to text excerpts within call transcripts. A text analytics solution would be able to match the name of the company to verify if the agent has said, “Hello, this is Level AI customer service.

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Chatbots Life

MARCH 16, 2023

Text analytics Text analytics is another data collection method that has gained popularity over the last few years due to advances in machine learning algorithms and extensive data processing capabilities.

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Flipboard

MARCH 22, 2023

Using these basics of prompt engineering, you can get the most out of generative AI.

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NLP People

MAY 18, 2018

DFKI LT lab conducts advanced research in language technology and develops novel solutions related to information and knowledge management, content production, speech and text processing. Key areas of their activity include text analytics, machine translation, human-robot interaction , and digital content creation.

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ODSC - Open Data Science

MAY 24, 2023

To save time for our financial advisors, our team decided to experiment with generative natural language processing (NLP) models to assist them in their daily conversations with clients. She has worked in several analytical domains, ranging from Retail and Urban Analysis to Customer Intelligence.

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Towards AI

JULY 19, 2023

Cloud Computing, Natural Language Processing Azure Cognitive Services Text Analytics is a great tool you can use to quickly evaluate a text data set for positive or negative sentiment. What is Azure Cognitive Services Text Analytics?

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ODSC - Open Data Science

MAY 9, 2024

Trending Large Language Models DBRX This model hopes to shake the world of large language models by setting a new standard for enterprise-grade natural language processing. Its key features include open-source accessibility, scalability, and seamless integration with the popular Databricks platform.

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ODSC - Open Data Science

OCTOBER 23, 2023

Traditionally, our NLP track has focused on the usual aspects of NLP, such as text analytics and sentiment analysis. While we still will have sessions on those topics, we’ve seen that LLMs are by far the most talked about topics in both AI as a whole, and specifically within the subfield of natural language processing.

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Pickl AI

AUGUST 1, 2023

Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python? Text mining is also known as text analytics or Natural Language Processing (NLP). Visualize the sentiment distribution and analyze trends and patterns in the data.

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ODSC - Open Data Science

SEPTEMBER 19, 2024

Streamlining Government Regulatory Responses with Natural Language Processing, GenAI, and Text Analytics Through text analytics, linguistic rules are used to identify and refine how each unique statement aligns with a different aspect of the regulation.

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Lexalytics

APRIL 5, 2021

Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. This is the sort of representation that is useful for natural language processing. I was out of the neural net biz. BERT is just too good not to use.

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Pickl AI

JULY 23, 2023

Text Analytics (Natural Language Processing) Text analytics, also known as natural language processing (NLP), involves extracting valuable information and insights from unstructured text data, such as customer reviews, social media posts, or survey responses.

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Pickl AI

JULY 20, 2023

Prescriptive Analytics Projects: Prescriptive analytics takes predictive analysis a step further by recommending actions to optimize future outcomes. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data. Create machine learning models to quickly identify and stop fraudulent transactions.

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SAS Software

AUGUST 6, 2024

When using LLMs, managing toxicity, bias, and bad actors is critical for trustworthy outcomes. Let’s explore what organizations should be thinking about when addressing these important areas. The post Toxicity, bias, and bad actors: three things to think about when using LLMs appeared first on SAS Blogs.

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SAS Software

DECEMBER 17, 2024

SAS' Mary Osborne, Ali Dixon Ricke, and Franklin Manchester break down what insurers still need to learn about generative AI. The post 10 things insurance leaders need to know about generative AI and LLMs appeared first on SAS Blogs.

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SAS Software

MAY 1, 2024

SAS' Federica Citterio answers the perennial data science question: "How can I trust (generative) LLM to provide a reliable, non-hallucinated result?" The post Five steps to improve information extraction using trustworthy generative AI appeared first on SAS Blogs.

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Flipboard

MARCH 10, 2023

As many of my readers know, not only do I come from an engineering and technical background, but I am also a…

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DataRobot Blog

MARCH 9, 2022

This is one of the reasons why detecting sentiment from natural language (NLP or natural language processing ) is a surprisingly complex task. It could be anything from a sentence to a paragraph to a longer-form collection of text. We use the term “document” loosely.)

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SAS Software

SEPTEMBER 6, 2024

We often hear about cyberattacks, hackers, ransomware, and other nefarious deeds in the news, but not all data breaches are caused by third parties. The post Three ways NLP can be used to identify LLM-related private data leakage and reduce risk appeared first on SAS Blogs.

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SAS Software

APRIL 4, 2023

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 [.]

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LevelAI

FEBRUARY 5, 2024

Organizations can delve deeper by utilizing sophisticated text analytics tools, identifying recurring themes, trends, and even specific language patterns within interactions. Many issues go unnoticed and unfixed. Quantifying the Qualitative: Customer service data extends beyond mere sentiment analysis.

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Explosion

FEBRUARY 14, 2016

If you were doing text analytics in 2015, you were probably using word2vec. For automatic natural language processing, it’s often more effective to use dictionaries that define concepts in terms of their usage statistics. Sense2vec (Trask et.

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