Semantic search is a very effective technology in the analysis of unstructured enterprise data. This article takes a closer look at how it can enhance and improve the search experience of users using an enterprise search software.
What is semantic search and how does it offer a path-breaking approach to analyzing enterprise data? It is a technology that involves analyzing the meaning of a query – bringing in synonyms and other similar words into the picture. This is poles apart from the traditional approach whereby the search engine only matches the terms in the query word by word and fetches the results accordingly. Semantic search, thus, works effectively to broaden the scope of the search engine and increase the accuracy of results. Also, a major share of the enterprise data is unstructured and this technology can be used to analyze it to derive meanings. This makes semantics a key component of new age enterprise search software like 3RDi Search, Algolia and Azure Search. This article talks about the many ways in which this technology enhances user experience.
1] Highly Enriched Results
The biggest impact that this technology brings is the huge enhancement in the relevancy of search results. A semantic search tool enriches the results and provides actionable insights that the decision makers of the business can take action on. Since a large portion of enterprise data is unstructured, semantic technology is the only way to go derive meaning and insights hidden deep within the data.
2] Context Driven Results
The same query can require entirely different results based on the context of the query. This makes the context a very key element in increasing the relevancy. With semantic technology and its capability to understand the context of the query, it becomes possible to leverage the relationship between entities in the data can be leveraged effectively to provide insights that are relevant to a specific domain. This enhances the quality of results to a large extent.
3] Faceted Search
While the search engine presenting pages of relevant results is fine, it is the user who is the best judge of relevancy, and so the user should have the option to apply filters to get the results that are most relevant to them. This is where faceted search comes into the picture. With semantic search technology, it is easy to offer the user multi-level filtered navigation, which makes it a rewarding experience.
4] Knowledge Graphs
Another huge contribution of the semantic search technology is the Enterprise Knowledge Graph that provides a higher level of contextual understanding. With knowledge graphs, it is possible to get the most relevant results through the aggregation of structured and unstructured data scattered across the enterprise.
5] Supports Scalability
Last but not the least, the deep insights that the semantic search platform offers a business, makes it possible for enterprises to make informed business decisions. Also, it offers search analytics, which improves the performance of the platform even as the business grows and evolves.
Hence, a semantic search tool can indeed have a path breaking impact on the way enterprises analyze and derive meaning of the unstructured data that they have. As the data grows in volume over each passing day, it becomes all the more challenging for enterprises to manage it without advanced semantic technology. The future holds unlimited possibilities when it comes to application of semantic search.
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