Almost all major search engines use machine learning, and it has also transformed enterprise search. The cross-industry impact of machine learning-enabled enterprise search has led users to expect machines to find what they need and bring it to them. To meet these user expectations, enterprises have to take advantage of smart taxonomies.
Users no longer search for information in the traditional way. They expect machines to find relevant content personalized for them automatically. To do this, enterprise search must serve the right content with insights into the users' topics. In addition, the search technology, from the taxonomy point of view, should be based on an in-depth understanding of the material and the ways of knowing.
To achieve this, enterprises must leverage smart taxonomies that deeply tag the content with context-specific and meaning-loaded entities, use smart summarization of the essential ideas, and smart distribution of insights. Subsequently, powered by learning what each user cares about, it finds the relevant material without being asked. The impact of machine learning trends on the socialization and utilization of competitive intelligence is all set to be profound and is poised to transform an enterprise’s competitive intelligence knowledge management system.
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