Meet two text mining experts in today’s interview, which explores some of the common issues faced by data scientists in text analytics. Prof. Dursun Delen and…
Added by Rosaria Silipo on November 15, 2020 at 12:00am — No Comments
The key to perform any text mining operation, such as topic detection or sentiment analysis, is to transform words into numbers, sequences of words into sequences of numbers. Once we have numbers, we are back in the well-known game of data analytics, where machine learning algorithms can help us with classifying and clustering.
We will focus here exactly on that part of the analysis that transforms words…
ContinueAdded by Rosaria Silipo on February 11, 2019 at 3:09pm — No Comments
I. Introduction
This is a continuation of my previous blog, “Natural Language Understanding – Application Notes with Context Discriminant”.
Background:
Natural Language Understanding (NLU) is a subtopic of Natural Language Processing (NLP). Successful implementations of NLU are difficult because of limitations in prevailing technology. SiteFocus solved these limitations with a new approach to NLU. This approach has been successfully…
ContinueSummary: The addition of AI capabilities to our personal devices, applications, and even self-driving cars has caused us to take a much deeper look at what we call ‘User Experience’ (Ux). A more analytical framework identified as Cognitive Ergonomics is becoming an important field for data scientists to understand and implement.
…
ContinueAdded by William Vorhies on October 31, 2017 at 9:51am — No Comments
Introduction
Business ventures based on existing or disruptive business models taking on the route of Initial Public Offering are always a challenge to investors who want to profit from early investment into those would be “unicorn IPO”. A good investment may get worse before it gets better. Others may get worse and never recover. Aside from the macroeconomics and consumer trends that could affect the outcome of such investments, the fundamentals of these new public offerings…
ContinueAdded by Sing Koo on October 31, 2017 at 2:30am — No Comments
Introduction
Deep Learning can be used to automate just about every repetitive task that is currently or formerly performed by humans. Factory robots, autonomous cars, Internet of Things are example of these automations. Yet, mentally challenging tasks such as conducting research or strategic planning with natural language textual documents remain a daunting task for automation. We look into the root cause of this challenge and have implemented a solution to automate these…
ContinueAdded by Sing Koo on October 6, 2017 at 1:00pm — No Comments
Text analytics can be a bit overwhelming and frustrating at times with the unstructured and noisy nature of textual data and the vast amount of information available. "Text Analytics with Python" published by Apress\Springer, is a book packed with 385 pages of useful information based on techniques, algorithms,…
ContinueAdded by Dipanjan Sarkar on July 14, 2017 at 4:00am — No Comments
This post covers the following tasks using R programming:
Added by Ann Rajaram on November 26, 2016 at 3:30am — 5 Comments
Added by Dalila Benachenhou on October 27, 2016 at 5:30pm — 2 Comments
How many times a day do we ourselves, or hear someone else, utter the phrase “Google it”? It’s hard to imagine that a phrase so ubiquitous and universally understood has been around for less than two decades. The word “Google” has become synonymous with online search, and when we think about why this, it’s because Google yields the most relevant, comprehensive results, quickly. Essentially, it has changed the way we find and interact with content and information.
We’ve seen the…
ContinueAdded by Tony Agresta on April 28, 2015 at 3:29am — No Comments
Organizations are struggling with a fundamental challenge – there’s far more data than they can handle. Sure, there’s a shared vision to analyze structured and unstructured data in support of better decision making but is this a reality for most companies? The big data tidal wave is transforming the database management industry, employee skill sets, and business strategy as organizations race to unlock meaningful connections between disparate sources of…
ContinueAdded by Tony Agresta on April 7, 2015 at 6:45am — 4 Comments
Summary: Gartner says that predictive analytics is a mature technology yet only one company in eight is currently utilizing this ability to predict the future of sales, finance, production, and virtually every other area of the…
ContinueAdded by William Vorhies on August 13, 2014 at 10:54am — No Comments
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