What is Google's strategy to stay ahead of its rival?
In this competitive global market of cutting edge technologies, one has to adopt new strategy and better technologies, very rapidly. This is the success mantra to stay ahead of rivals. Following this rule of success and for beating its rivals, Google is introducing a new search engine strategy so-called "sematic search" technology. This upcoming technology from Google will defnitely impact the existing SEO techniques. Semantic technology compelling internet users, especially bloggers and website developers to frown as this search engine technology can make impact their revenue raising policy.
Bloggers and contents developers should start to learn new SEO techniques as Semantic search expected to launch in near future. Eventhough, Google had already started experimenting Semantic search technology through serives like: Google Instant. But by adopting few new strategies, as described in Learn Google semantic search algorithm to earn high Adsense revenue, you can continue to raising your present revenue.
What is Semantic Search?
Though a number of well written articles on semantic search like What is Semantic Search?, covering very important aspects of this topic, have already been posted at this website yet here we are going to describe semantic search in some more ways for making it more clear to you:
For example - If you ask a semantic search engine "When India got its constitution?" it might answer like "India got it constitution on January 26, 1950", instead of referring you a long list of web pages or documents links that contain the words "constitution" and "India". Hence, Semantic search is a strategy to keep the Google search box not only a text receiver and webpage links provider but to extend its intelligence to a giant leap.
Unlike existing search engine technologies that compare a query against a constantly-updated index of documents or web pages, the semantic search engine compares it against precompiled and discrete knowledge sets, where knowledge sets describe the relationships between items in the knowledge base.
How does semantic search differ from Literal search?
Search engines are designed to search documents for specified keywords and return a list of the links to webpage, file, documents etc., where it finds that keyword. In contemporary typical search engines, a spider (program) is sent to fetch as many documents as possible. Then Indexer (another program) is used to read these documents to create an index based on the words contained in each document. But now, the world of internet searching is going to break down in two categories, based on their searching strategies and intelligence:
Literal search: At present, literal search strategy is used for search engines. It returns all matching items like webpage and documents etc. based on the matching for some or all keywords input by the searcher to the search textbox. For searching, a number of things can be augmented such as - association and conjugation for expanding or restricting the searching. Literal search, sometimes also termed as Navigational search.
Semantic search: In semantic search, first of all search engine tries to understand the meaning of user's query. It places the keywords in context, through analysis of the query's terms and language. This is a tightly pre-compiled knowledge based analysis, along with knowledge about the user. Secondly, instead of returning a set of web pages, files or documents etc., semantic search tries to provide a direct answer to the searcher's query.
How does Semantic search superb over existing Literal search technology?
Both Sematic as well as Literal search technologies are used for the same purpose, but each one has its own importance in respect to the searching tasks. For example – if you are looking for a specific thing like – a webpage, document, file, discrete item or an album etc., Literal search works great. On the other hand, for searching specific information like – time, date, place, name or a specific thing, Semantic search works really excellent.
But while comparing both strategies in respect to superiority, Sematic search found better for providing direct information, instead of providing you a number of links for navigating to find out exact information that you intent to search. Google's Semantic search engine is an upcoming future technology with integration of Artificial Intelligence and based on Knowledge Graph Repositories.
There is no doubt that existing search engines working great in existing scenario; but for future generation of far more advance technologies such as artificial intelligence, semantic technology will be the better option for search engines.
As per Google, "Semantic search technology could provide direct answer to between 10 to 20 percent of Web searches." A running number of tests are being carried out at Google R&D centre for estimating capability of Semantic search technology. Again as per Google, "They handled 11.7 billion searches in United States alone in February 2012. With semantic search capabilities, more than 2.3 billion of those searches could have been answered directly, instead of sending people off to other Web pages and sites."