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Recently, Google and other innovators have been developing and experimenting with natural language processing with the goal of applying that technology to their search engines. The results are known as "semantic search".

Semantic search methods could improve traditional results by using, not just words, but concepts and logical relationships.

Most of the early efforts on semantic-based search engines were highly dependent on natural language processing techniques to parse and understand the query sentence. One of the first and the most popular of these search engines is Cycorp.

Cyc combines the world's most massive knowledge base with the Web. Cyc (which takes its name from en-cyc-lopedia) is an immense, multi-contextual knowledge based. With Cyc Knowledge Server it is possible for Web sites to add common-sense intelligence and distinguish different meanings of vague concepts.

Latent Semantic Indexing as an Approach to Semantics

LSI is a method of retrieving information that organizes existing content into a structure that uses implicit higher-order associations of words with text objects. The resulting structure reflects the significant associative patterns in the data. This permits retrieval based on the 'latent' semantic content of the existing Web documents, rather than just on keyword matches.

LSI offers an application method that can be implemented immediately with current Web documentation. In a semantic network, the meaning of content is better represented, ambiguity can be removed and logical connections are formed.

How Semantic Search Improves Search Accuracy

In a word, semantic search is about accuracy. It focuses on the context of a query (previous searches), search intent, location and the variation of queries to deliver relevant and precise search results.

Semantic search, in fact, is the ability of a search engine to determine what you mean when you type a query and then return search results that do not necessarily match with the entries or words you have entered into the query box. See examples of this here.

Capacity to understand the content of the web pages is the prime feature of semantic web search.

However, most semantic network-based search engines suffer performance problems because of the scale of the extensive semantic network. For the semantic web search to be useful in finding responsive results, the system must contain a great deal of relevant information. At the same time, a vast network creates difficulties in processing the many possible paths to a suitable solution.

What Semantic Search Looks Like in Google Results

Semantic SEO is a new frontier for search engine optimization experts who want to stay ahead of the Google curve in securing additional search engine rankings for their websites. 'Semantic SEO' is currently misunderstood by large parts of the SEO community. Once understood, the proper application of a Semantic SEO strategy for your website (and for your clients) can pay big dividends in improving your on-page performance and deliver increased (qualified) site traffic for search engine queries containing alternate word meanings.

A prominent example of an alternate word meaning is searching Google for the term "turkey cutting". If you perform this search, you will see that all of the sites which are ranking on page 1 of Google for this term reference carving turkeys, not cutting them.

turkey cutting SERP

This is a simple example of Google knowing that you are looking for the best way to carve up your bird when you request ways to cut it. More importantly, for the websites ranking page 1 on Google for this term, they're getting the traffic from the search query because they are (often unknowingly) using a better alternative word in their original copy.

Google applies 'semantics' (aka synonyms or alternate word and phrase meanings) in a unique way to its search results. Traditionally, the use of semantic indexing of content borrows from the application of LSI which makes use of an ontology or thesaurus to offer alternate meanings for words. The thesaurus or ontology contains specific alternative word meanings for the target word.

What Semantic Search Is and Is Not

Google stores trillions of pieces of data on user searches, so they know better than a thesaurus what people are searching for, and the alternate search meanings that deliver accurate search results in the real world of online search. In fact, they have their internal method for determining semantic relevance.

This has significant implications for SEO experts and marketers who are interested in ranking in Google for additional queries. Simply inserting synonyms for a keyword from the thesaurus does not guarantee better Google organic search traffic. The best case scenario is that you take some of the alternate words, but will also include words that Google does not think are semantically relevant, and you'll miss words completely that Google knows are relevant to searchers.

For websites and SEO firms looking to get serious about semantic analysis to drive more targeted keyword traffic, the right approach is the creation of a semantic map which places your target search terms at the center of the map and analyzes primarily related phrases for the words. Besides, it adds a second layer of analysis to each of those secondary terms to give you a complete viewpoint of the alternate keywords and phrases that you can and should use.

Semantic phrases offer several powerful SEO options to a website, from inclusion in page titles and HTML headers to varying backlink anchor text with semantically relevant keywords, to the addition of new internal pages for semantic topics which you then point to the target page to increase its reputation and semantic relevance.

Impacts of Semantic Search Engines on SEO

A lot of SEO techniques have changed drastically in the recent times in the context of Google algorithm updates like Panda and Penguin. One thing has, however, remained fairly unabated all the same amid a wave of changes. SEO world is still primarily driven by keyword targeting. Use of keywords in URL structure, meta tags, links and content is still seen.

However, semantic web search is adding a whole new element to this world: the human element. Now, SEO professionals are must base optimizations on the actual meaning of the keyword they are using and to create content accordingly.

This means focusing more on creating content that is relevant to the keyword topic, not just the keyword. It also means a greater priority will be placed on matching content to the user’s search intent. That will mean answering questions thoroughly, providing detailed instructions and creating optimized and targeted landing pages.