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Google Hummingbird and Semantic Search

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Google, as we all know, is the top ranked search engine that leaves all its competitors far behind in terms of quality score and popularity. Google is on a constant hunt for the most advanced search algorithms to stay at the forefront. Google Hummingbird is the latest change in search Algorithm done to improve the accuracy of search. Let us look at Google Hummingbird and its semantic search capabilities. Google Hummingbird algorithm is confirmed to be equally effective for conventional and semantic search. Semantics, as the word suggests, is the study of relationship between words and phrases used and its syntax. Semantic search helps to identify the contextual meaning and denotation of the words used in a content. For each search, relevant results are generated, no matter whether the content is on a closed system or in the worldwide web. Basically Google is on a quest to find relationships between how people search and the importance of giving the correct results depending on the relationships between words and their content.

How does Semantic search Work? In









technology with a view to identify the real intent of the searcher. The results presented will therefore be closely related to what the user is looking for. The final search results are presented only after identifying the proper association between the terms used in search query. Semantic search is mainly applied to deal with complex or ambiguous queries. These queries are processed in such a way as to help the search engines grasp the real context of the query. Semantic search is used with regard to research related queries - cases where the user is seeking answers instead of moving on to a particular web page. Google’s Knowledge Graph uses semantics. Google Hummingbird algorithm follows a statistical approach. It processes the complete statement of query and finds out the most

appropriate webpage that contains the answer for it. The algorithm also has the capability to handle knowledge matching, synonyms, concept matching, and generalizations.

How it is Significant to SEO Search engines like Google originally used to consider page rank and relevancy as the two most important criteria to determine the ranking of a webpage.

Page rank is dependent on the popularity of a page

based on its backlinks and relevancy is determined by the use of search query terms and keywords. But such a webpage ranking methodology is not found successful at all times. Certain websites that have relevant content are missed out in such cases. This has led to the launch of Hummingbird algorithm that uses semantics to prioritize the rank. As mentioned earlier, Google Hummingbird is a revolutionary attempt to deliver precise and exact search results. It has the ability to handle highly complex search requests and provide quick answers. According to Google, websites with original and high quality content need not worry about the new innovation since Hummingbird is designed only to process information in a different way. SEO experts point out that Google










preoccupation is with the quality of the content on the web page. Hummingbird is likely to have a negative impact only on those websites that follow unethical tactics to achieve their goals. SEO should focus on ensuring superior quality content that will appeal to both search engines and humans, which in turn will ensure high ranking for such content and more shares.

Google Hummingbird and Semantic Search  
Google Hummingbird and Semantic Search  

Google Hummingbird uses semantic search to return the best search results. Hummingbird is likely to have a negative impact only on those web...