KM World White Paper

Cognitive Search Brings the Power of AI to Enterprise Search

Sinequa contributed to a KMWorld White Paper on “Best Practices in Cognitive Search”. Here are some extracts from this contribution:

Forrester, one of the leading analyst firms, defines Cognitive Search in a recent report¹ as: The new generation of enterprise search that employs AI technologies such as natural language processing and machine learning to ingest, understand, organize, and query digital content from multiple data sources.

Here is a shorter version, easy to memorize: Cognitive Search = Search + NLP + AI/ML
In this equation, “search” is not the old keyword search but high-performance search integrating different kinds of analytics. Natural Language Processing (NLP) is not just statistical treatment of languages but comprises deep linguistic and semantic analysis. And AI is not just “sprinkled” on an old search framework but part of an integrated, scalable, end-to-end architecture.

For AI and ML algorithms to work well, they need to be fed with as much data you can get. A cognitive search platform must access the vast majority of data sources of an enterprise: internal and external data of all types, data on premises and in the cloud. Hence the system must be highly scalable.

Hans-Josef Jeanrond, CMO at Sinequa

(1) Forrester Wave: Cognitive Search & Knowledge Discovery Solutions, Q2 2017 (Download here)

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