Semantic technology or semantic search as it is known as, is one of the key technologies powering enterprise search software today. This article is all about how semantic search works to add to the search experience of users who look for relevant information from enterprise data.
The word semantic means ‘meaning’ and semantic search means focusing on the meaning of a term in order to bring the most relevant results. Search has come a long way from the days of yore when the keyword-based approach was the norm and it was all that people had in order to find the information they wanted. However, technology has evolved a lot ever since, and today NLP, AI, machine learning and semantic technology are the key concepts in the world of data science, search and enterprise data. Organizations across the globe are waking up to the necessity of advanced search engines like 3RDi Search, AddSearch and Algolia that are powered by these technologies in order to deal with and make the best use of the ever growing volumes of data.
Semantic search is important because it’s powerful when it comes to analysis of unstructured data, and most of the data that enterprises have today is unstructured. However, organizations cannot afford to ignore this data altogether because it often contains deep insights hidden within – insights that can help enterprises come up with important business decisions. This article is all about the many ways in which semantic search engines can redefine the experience for the users.
1] Results that are Context Driven
2] Faceted Search for More Refined Results
3] Enterprise Knowledge Graph for Important Insights
4] Insights to Make Best Use of Business Data
5] Scalability to Face the Challenges of the Future
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