Articles
Frustration and dissatisfaction are common emotions when it comes to enterprise search. Why is that the case?
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Usually when there's an issue with search, the problem lies in how it's configured, implemented or managed. But occasionally, you'll need a new platform.
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Search is not a fire and forget it technology. It takes time and resources to maintain high quality user satisfaction.
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The term "insight engines' is used to describe extended enterprise search capabilities. What do they do, and where does the Apache Software Foundation fit in?
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Certain words that come up within the enterprise search context are used interchangeably — here they are and how they differ.
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When you first introduce machine learning to your enterprise search, you’ll inevitably make some mistakes.
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Vendors now integrate selected open source projects to deliver specific capabilities, along with a licensed proprietary commercial platform.
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Companies devote time and money to perfecting their website's SEO. Now it's time to devote some of the same resources to internal search.
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A profile of one of CMSWire's contributors of 2018, Miles Kehoe.
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By layering proprietary user interfaces on top of open source kernels, enterprise search vendors free their engineers to focus on what users buy: the UX.
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Proprietary enterprise search vendors are increasingly integrating open source tools under the covers.
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Machine learning can improve enterprise search results — but only if you take the time and effort required to train and tune it.
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Applying machine learning and artificial intelligence to search.
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Another shift in the enterprise search space from search engine to insight engine.
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