What do Google algorithms mean for semantic search?
Google's algorithms play a crucial role in determining the relevance and accuracy of search results for semantic search queries. Semantic search is a method of understanding the intent behind a user's search query and returning results that match that intent, rather than just matching keywords.
Google's algorithms have evolved to better understand the meaning behind search queries, through techniques such as natural language processing and machine learning.
For example, Google's BERT algorithm, which stands for "Bidirectional Encoder Representations from Transformers," is a neural network-based technique that is trained to understand the context of words in a sentence. This helps Google to understand the intent behind a query and return more relevant results.
Additionally, Google's algorithms also take into account the relationships between words, concepts, and entities. This is known as knowledge graph, which is a database of information about people, places, and things, and how they are related to one another. By using knowledge graph, Google is able to understand the context and intent behind a query, and return results that are more relevant to the user.
Another important aspect that Google algorithm take into account is the relevance of the webpage, the relevancy of webpage is determined by various factors such as page's content, the number of inbound links, and the overall authority of the website.
Overall, Google's algorithms are constantly evolving to better understand the intent behind semantic search queries and return more relevant and accurate results. This is beneficial for both users, as they are more likely to find what they are looking for, and also for businesses and website owners, as their websites are more likely to be seen by potential customers.