DataScava

06/27/2023

Here's our article published in CDO Magazine: "Machines in the Conversation: The Case for a More Data-Centric AI," commissioned by DataScava and TalentBrowser from Scott Spangler, former IBM Watson Chief Data Scientist, named IBM Engineer, and author of the book Mining the Talk: Unlocking the Business Value in Unstructured Information. See our DataScava website for Scott's full series of articles about our three methods that pinpoint the data you care about:

DSIndex Domain-Specific Language Processing (alternative to NLP)
DSTopics Tailored Topics Taxonomies (encapsulate your expertise)
DSMatch Weighted Topic Scoring (filter and match using your criteria)

https://www.cdomagazine.tech//opinion-analysis/machines-in-the-conversation-the-case-for-a-more-data-centric-ai

04/26/2023

In this article, Scott explains the drawbacks of using a pure Machine Learning/NLP approach to RPA and then explains the need for customer understanding through three fundamental capabilities: classification of content, characterization of the customer, and customization of features. Scott illustrates how DataScava technology can be employed to fill in these critical gaps and provide a better customer experience by readily capturing existing in-house expertise.

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the difference between knowing and understanding when it comes to implementing Robot Process Automation. Scott is a former IBM Watson Health Researcher, Chief Data Scientist, and the author of the book “...

04/26/2023

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the importance of fully utilizing Unstructured Data in Business Intelligence analytics. Scott is a former IBM Watson Health Researcher, Chief Data Scientist, and the author of the book "Mining the Talk: Unlocking the Business Value in Unstructured Information."

This article provides an overview of the most common current approaches to analyzing unstructured information in BI — Machine Learning, Generic Taxonomies and Text Mining — highlighting the specific drawbacks of each. It then explains the importance of subject matter expert-driven taxonomies and illustrates how DataScava can be used to build and deploy these taxonomies at scale and mine unstructured data to maximize business value.

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the importance of fully utilizing Unstructured Data in Business Intelligence analytics. Scott is a former IBM Watson Health Researcher, Chief Data Scientist, and the author of the book "Mining the Talk: Un

04/26/2023

I'm here with Scott Spangler, former IBM Watson Health Researcher, Chief Data Scientist, Distinguished Engineer and author of “Mining the Talk: Unlocking the Business Value in Unstructured Information.” We’re discussing how DataScava's domain-specific approach to unstructured text mining complements real-world big data applications in Artificial Intelligence and Machine Learning.

November 15, 2021 I'm here with Scott Spangler, former IBM Watson Health Researcher, Chief Data Scientist, Distinguished Engineer and author of “Mining the Talk: Unlocking the Business Value in Unstructured Information.” We’re discussing how DataScava's domain-specific approach to unstructured...

02/26/2023

Here's our new article "Machines in the Conversation: The Case for a more Data-Centric AI."

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the latest developments in generative AI. Scott is a former IBM Chief Data Scientist and author of the book "Mining the Talk: Unlocking the Business Value in Unstructured Information."

In this article, he argues that too much focus on generative AI distracts from the important value a more Data-Centric AI approach can provide to business applications. He then discusses the key technologies that we use to enable such an approach within the organization:

✔️ Topic models which reflect the primary areas of focus;
✔️ Flexible topic scoring to encode the organization's priorities;
✔️ Customized text processing that mirrors the way people actually communicate in the industry.

Learn more at https://datascava.com/

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the latest developments in generative AI. Scott is a former IBM Chief Data Scientist and author of the book Mining the Talk: Unlocking the Business Value in Unstructured Information.

02/26/2023

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the latest developments in generative AI. Scott is a former IBM Chief Data Scientist and author of the book "Mining the Talk: Unlocking the Business Value in Unstructured Information."

In this article, he argues that too much focus on generative AI distracts from the important value a more Data-Centric AI approach can provide to business applications. He then discusses the key technologies that we use to enable such an approach within the organization:

✔️ Topic models which reflect the primary areas of focus;
✔️ Flexible topic scoring to encode the organization's priorities;
✔️ Customized text processing that mirrors the way people actually communicate in the industry.

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss his views on the latest developments in generative AI. Scott is a former IBM Chief Data Scientist and author of the book Mining the Talk: Unlocking the Business Value in Unstructured Information.

03/17/2022

This is the * first * in a series of articles DataScava commissioned from the brilliant Scott Spangler, former IBM Watson Health Researcher, Chief Data Scientist, and author of the book 💥 “Mining the Talk: Unlocking the Business Value in Unstructured Information.” 💥

Scott discusses how DataScava's patented domain-specific approach to unstructured text data mining complements real-world applications in AI, ML, RPA, BI, Talent and Research. Read his Q&A and the full series on our website.

DataScava commissioned named IBM Distinguished Engineer Scott Spangler to discuss how our patented domain-specific approach to unstructured text mining…

01/12/2020

"As companies double down on business initiatives built around technologies like predictive analytics, machine learning, and cognitive computing, there’s one element they ignore at their peril — humans," according to two MIT experts. Here are their 5 steps to keep your AI "people-centered."

1. Classify what you’re trying to accomplish with AI.
2. Embrace transparency, explainability and reversibility.
3. Establish data advocates because “garbage in, garbage out” holds.
4. Practice “mindful monitoring” of your data sets.
5. Ground your expectations and focus on a people-oriented AI agenda.

Artificial intelligence should amplify human strengths. Here’s a roadmap for developing systems that do just that.

08/15/2019

Got unstructured text data? Check out our guest post for KDnuggets describing how our Domain-Specific Language Processing and patented Weighted Topic Scoring can be your alternative or adjunct to NLP to mine valuable information from data by following your guidance and using the language of your business.

Processing unstructured text data in real-time is challenging when applying NLP or NLU. Find out how Domain-Specific Language Processing can also help mine valuable information from data by following your guidance and using the language of your business.

06/06/2019

DataScava's patented “Weighted Topic Scoring” finds the most relevant documents from large data sets, providing highly precise results you can see, control and measure. Visit our website to learn how https://datascava.com/.

04/16/2019

If your performance plan includes any of the following:

1. Increase Efficiency of Data Scientists
2. Increase Accuracy of unstructured data Searches
3. Reduce Risk of AI/ML Suggested Actions
4. Satisfy Regulators requirements for explaining AI/ML output
5. Build leading edge systems to identify the most viable documents within large unstructured data sets

If you strive for Excellence in any of these areas..... read on.

Real-time mining of unstructured textual content isn’t simple. Available solutions don’t work well unless they’re fine-tuned to meet your specific needs and address the unique quirks in your company’s information.