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7 Benefits of AI-based Search Assistance (Video)

In his presentation at KMWorld 2018, Trevor Cookson, M-Files AI product manager, explained the importance of AI-based search assistance. 

“We are dealing with this massive explosion of volume,” Cookson said, asking, “How many of us go past the first page on Google when we're searching for anything?” 

Cookson outlined characteristics of AI search assistance capabilities and what they each mean and their purpose:

  • intelligent type ahead
  • query attribute expansion
  • concepts/topic matters
  • personalized reference sorting
  • related documents
  • similarity
  • summarization

“There is no one silver bullet,” said Cookson. “It's kind of a simplistic thing, but the more you know, the smarter you are. And as basic as a statement that is, you have to continually just learn small aspects of the document and what to do with it. 

For example, he noted, “I heard some talk today about summarization, saying sometimes it works, sometimes it doesn't. There are extractive summaries and then there are some that are built on the fly. If you ask three people to read the same document, and you asked them for a summary of the document, do you think any one of them are going to be exactly the same? It's an impossibility.” 

But, the idea is to save people the trouble of having to open a document up to see if it is what they think they are looking for, said Cookson, and that is all that is needed. 


Watch the complete video of this presentation in the KMWorld Conference 2018 Video Portal. 

Many speakers have made their presentations available at www.kmworld.com/Conference/2018/Presentations.aspx.

Learn more at KMWorld 2019, coming to Washington, DC, Nov. 5-7.

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