Semantic search is summarised as ‘search systems that consider various points including the context of the search, location, intent, variation of words, synonyms, generalised and specialised queries, concept matching and natural language queries to provide the most relevant search results’. .Semantic Search, as it is used in current parlance is essentially the notion of using or exploiting metadata to improve search on documents. In the case of search engines, it more explicitly refers to embedding metadata in HTML5 (using semantic markup, the formats or HTML5 syntax currently supported by the search engines: RDFa Lite and microdata).
A good example of this is the search term ‘hair of the dog’ which we all know is an expression used as a method for getting rid of a hangover. In years gone by it is likely that the results provided to the user would be based around dog hair however now search algorithms understand that the most relevant results for the user would be based around hangover cures.
Good definition of Semantic SEO-It is the use of techniques from the Semantic Web technology stackfor:1.sending detailed information about the meaning of yourpage content to search engines and other data consumers,2. in a way that can be easily processed by computers.
Data organized by a markup language and avocabulary. Can be organized and searched by machines.
Publishing structured data so it can be accessedat a URI
The web of globally accessible, interlinkeddata entities
This is a data modelthat establishes entity relationships using ‘triples’ Other notable parts of the ‘Semantic Web Technology Stack’
One example is that of enhanced displays in the SERPs − Google’s Rich Snippets, Bing Tiles or Yahoo SearchMonkey. Enhanced displays also provide more visually engaging displays and interfaces with a corresponding increase in CTR.
Another aspect of exploiting this information for search engines is to search directly on this consumed metadata – examples would include Sindice.com or Google with the Knowledge Graph and the Knowledge Carousel.
This is a large part of the evolution of search engines from producing a series of probabilistic results or “blue links” to becoming “answer engines.” Users definitely find it tiresome running multiple queries to obtain (or not) an answer to a query. Relevancy in answer to a query is everything, and there are multiple ways semantic technologies can be leveragedto ultimately attain that goal.
Determining user intent is yet another means of exploiting semantic technology. It can be done by:
Producing or publishing this information in the form of embedded metadata in, say, HTML5 can be accomplished via adding microdata or RDFa Lite as defined in the Google blogs and other blogs. However, these are merely syntaxes that can be consumed or understood by the search engines and are HTML5 compatible.
The other issue is that of vocabularies (or ontologies or taxonomies). Since standards are always an advantage in many arenas, the three search engines − Google, Bing and Yahoo − agreed to mandate a standard vocabulary or ontology, that of schema.org, announced June 2, 2011. Search engines have such a large user base that they actually have the power to mandate the ontologies or vocabularies to be used.
The Semantic Web community has many other defined ontologies/vocabularies and provides them as open source (GoodRelations for e-commerce, FOAF SIOC, Wordnet, DBpedia – derived from Wikipedia and more).
Schema.rdfs.org has a great set of resources for those of you wanting to get started as there are tutorials, software and tools to generate structured markup automatically, and more.
Depiction of the Knowledge Graph combined with features of the Knowledge Carousel, namely the scroll bar on the top. The Knowledge Graph is extended from simply Freebase and other linked data sources via validated verified pages and trusted sources containing structured markup as per Semantic Web related techniques.
The query entered for the display below was “Tom Cruise Movies.” The Knowledge Carousel is globally available in English as of September 2012.
Note the depiction of results for the band “Coldplay.” Rich snippets markup for schema.org (music, etc.) is clearly integrated into this display.
The examples are certainly indicative of how these enhanced displays consume SERP real estate.
Another crucial aspect of Semantic SEO or schema is the increase in CTR for marked up items, and the incredible increase of screen real estate utilized by the Knowledge Graph/Carousel and Rich Snippets and other information aggregated by Google (like places and events on the RHS of Google, where the Knowledge Graph results typically display).
Example shown below:
In summary, Semantic SEO and Semantic Technologies bring many strong benefits to the search engines.
Future articles in this series will dive into the specific verticals in greater depth, clarifying in more detail how vertical search improves relevancy and defines user intent, taking a look at semantic technologies used in recommendation engines, semantic advertising and more!
This makes it ultra-easy to validate any page for rich snippets
Another key element of semantic ‘link building’ is to build out your relevance to widen the scope of what you are ‘about’. If Google is looking to diversify results then the more words and phrases you can associate yourself with the better.
This means expanding your repertoire. Writing more about those peripheral semantic phrases that are still on brand but may help you rank for a greater number of related searches.
In many ways this is not dissimilar to how any good content strategy should be constructed anyway but below are a few simple reminders and additional points to consider when designing content for a semantic engine:
Keywords are easy to manipulate; intent, not so much. In order to rank well in search, you don’t just have to put your keywords in the right places, you have to figure out the actual meaning behind those keywords and create content around that specifically. That puts more emphasis on your keyword research.
When people search, they aim to answer a question. They just search in the truncated version of that question. Keyword research is largely data-driven around the popularity of the terms in their question. Keyword research in semantic search will have to focus on what that person actually means when searching for that keyword.
The first thing you must work on when considering your off page plan of attack to proactively improve your own relevance profile is to understand what is considered ‘relevant’ to you, and how, in a semantic world. Below is an example of related words to ‘content marketing’ and how they are connected:
Tools exist to take the hard work out of the process and a few of the best are listed below:
http://ctrl-search.com/blog/ – this is a great tool to enrich your on page content. Effectively semantically optimizing your own site. By pasting in snippets of your post the engine finds semantically associated images and other content for you to link out to and add.
http://lsikeywords.com/ – a few great blog posts have been created recently around the subject of LSI, or Latent Semantic Indexing, including this one linked to on our own blog.
LSI Keywords is one of a handful of tools that will present a list of semantically relevant keywords and phrases for you to widen your outreach approach.
http://bottlenose.com/ – is a tool I have mentioned before here and its great for a multitude of things, especially big data led content cu ration. One of its ‘tools’ however is great for understanding degrees of relevance separation. Once you type in a keyword you have the option to scroll through a number of different tools but the one that we want to use for this is the Sonar+. It visually maps real time semantic relationships between concepts based on Twittersphere sharing and other big data.
Google Semantic Operator – not a tool per se but a really useful operator to help define semantic keyword relationships. By adding the ~ Tilde symbol when searching Google for your key phrase (e.g.: ~travel) you will see other words that Google has mapped against that word, such as Hotels, Flights, Holiday, Tours.
http://ubersuggest.org/ although it is not officially a semantic tool ubersuggest is built on Google predictive search engine and so by default it delivers semantically relevant searches, which makes it great for building outreach keyword lists.
All of the above tools give the user the ability to create a keyword-based map of where to outreach to if links are your project aim.