Utilizing machine learning to uncover the right content at KMWorld Connect 2020 – KMWorld Magazine

At KMWorld Connect 2020 David Seuss, CEO, Northern Light, Sid Probstein, CTO, Keeeb, and Tom Barfield, chief solution architect, Keeb discussed Machine Learning & KM.

KMWorld Connect, November 16-19, and its co-located events, covers future-focused strategies, technologies, and tools to help organizations transform for positive outcomes.

Machine learning can assist KM activities in many ways. Seuss discussed using a semantic analysis of keywords in social posts about a topic of interest to yield clear guidance as to which terms have actual business relevance and are therefore worth investing in.

What are we hearing from our users? Seuss asked. The users hate the business research process.

By using AstraZeneca as an example, Seuss started the analysis of the companys conference presentations. By looking at the topics, Diabetes sank lower as a focus of AstraZenicas focus.

When looking at their twitter account, themes included oncology, COVID-19, and environmental issues. Not one reference was made to diabetes, according to Seuss.

Social media is where the energy of the company is first expressed, Seuss said.

An instant news analysis using text analytics tells us the same story: no mention of diabetes products, clinical trials, marketing, etc.

AI-based automated insight extraction from 250 AstraZeneca oncolcogy conference presentations gives insight into R&D focus.

Let the machine read the content and tell you what it thinks is important, Seuss said.

You can do that with a semantic graph of all the ideas in the conference presentations. Semantic graphs look for relationships between ideas and measure the number and strength of the relationships. Google search results are a real-world example of this in action.

We are approaching the era when users will no longer search for information, they will expect the machine to analyze and then summarize for them what they need to know, Seuss said. Machine-based techniques will change everything.

Probstein and Barfield addressed new approaches to integrate knowledge sharing into work. They looked at collaborative information curation so end users help identify the best content, allowing KM teams to focus on the most strategic knowledge challenges as well as the pragmatic application of AI through text analytics to improve both curation and findability and improve performance.

The super silo is on the rise, Probstein said. It stores files, logs, customer/sales and can be highly variable. He looked at search results for how COVID-19 is having an impact on businesses.

Not only are there many search engines, each one is different, Probstein said.

Probstein said Keeeb can help with this problem. The solution can search through a variety of data sources to find the right information.

One search, a few seconds, one pane of glass, Probstein said. Once you solve the search problem, now you can look through the documents.

Knowledge isnt always a whole document, it can be a few paragraphs or an image, which can then be captured and shared through Keeeb.

AI and machine learning can enable search to be integrated with existing tools or any system. Companies should give end-users simple approaches to organize with content-augmented with AI-benefitting themselves and others, Barfield said.

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Utilizing machine learning to uncover the right content at KMWorld Connect 2020 - KMWorld Magazine