At its core, enterprise search is a solution completely owned by your business. It acts as the central hub, linking people to the knowledge they need to effectively perform their job duties.
While the challenges can vary from one company to another, enterprise search can reflect the company’s culture, capabilities, and struggles. For example, company culture can be based on region, industry, products, organizational size, and/or the leadership team.
To be clear, enterprise search is not the same as commercial search engines like Google or Bing. It’s also more than basic indexing. Instead, enterprise search can be customized with your data and include a personalized search experience that answers queries within a context relevant to your organization.
Components of enterprise search.
Content awareness: Regardless of the storage system, users are provided access to every piece of content they need.
Content processing: Content processing comes into play when all documents are processed in a format the enterprise search engine can understand. In addition, content is normalized to help ensure the accuracy of search results and recall.
Indexing: The point of indexing is to enhance flexibility. When organizational content systems are connected, the textual content is stored in an index, AKA, an enterprise search engine. Still, it is critical for the enterprise search engine to scale along with your organization. Thus, cataloging into multiple indexes helps to improve flexibility. It also helps to streamline disparate repositories into one system. In terms of finding relevant data, meta tags play a crucial role.
Query processing: Any term or interface, such as a web portal, a user enters to perform their queries.
Matching: The query is matched against the current index to find relevant results. For instance, the search starts with a query, which could be a natural language question or a set of keywords. Within the query could be data including a user’s geolocation, browser, search history, device, and more. If it is a known user, then permissions may be applied to offer access to more complex and varying data sources. Then, the enterprise search engine will find and rank results based on how well they match the query.
NLP: Natural language processing is the ability of computer systems to analyze languages humans speak and type naturally utilizing artificial intelligence.
Entity extraction: With the entity extraction functionality, elements are located and classified by predefined categories such as percentages, money values, quantities, names of persons, organizations, locations, and more.
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