Semantic search refers to the ability of search engines to consider the intent and contextual meaning of search phrases when serving content to users on the web.
At one time, search engines could only analyze the exact phrasing of a search term when matching results with a search query. Now, search algorithms are more sophisticated and incorporate semantic search principles when ranking content.
We often talk of semantic search as if it’s something new. It’s not. When search engines first started, keywords were the main ranking factor. Usually, a page that repeated the target search term the most times would get top placement on search engine results pages. The old search system also made it difficult for users to find relevant information because search engines couldn’t properly decipher the context and meaning of search queries. They could only analyze and produce exact match results.
The development of artificial intelligence (AI) and natural language processing technologies have changed the way a search engine retrieves information.
Semantic relationships are strengthened by professional annotators who hand-tune the results, and the algorithms that generate them. Web searchers tell the algorithms which connections are the best through what they click on.
Semantic search has made topics, not just individual keywords, very important. Search engines strive to serve the most valuable and relevant results to users, so content must be more comprehensive and informative than ever before.
By improving core natural language processing technologies for automatic information extraction and classification of texts, search engines built on these technologies can continue to improve.
Semantic technology and AI language continue to evolve and be used in a variety of applications.
Semantic search aims to get at the real intent of the query, rather than simply matching a page to a search string. It would be easy to assume that semantic search will be superior to the word matching, index-based approach.
Google has been using basic synonyms as part of the Knowledge Graph. This thesaurus-approach to zeroing in on the real meaning is based on taxonomy principles.
It has never been more important to have someone with the expertise and knowledge handling your content, developing your taxonomies and making your information findable. Access Innovations is one of a very small number of companies able to help its clients generate ISO/ANSI/NISO compliant taxonomies to produce comprehensive results.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
