In the ever-evolving landscape of search engine optimization (SEO), Google is constantly updating its algorithms to provide the best possible search results to its users. One such development is Google’s focus on information gain scores, as discussed in Bill Slawski’s article, “Ranking Search Results based on Information Gain Scores.” Bill Slawski, a subject matter expert in Google patents, has made significant contributions to the SEO community with his in-depth analysis of Google patents and their implications on search engine algorithms. In this blog post, we’ll discuss the concept of information gain scores and their potential impact on the SEO landscape.
The Importance of Information Gain Scores:
Google’s patent application on information gain scores aims to address the issue of search results providing users with repetitive or redundant information. When users search for a topic, they often encounter multiple documents with similar content. Information gain scores measure the amount of new information a source provides to a user who has already seen other sources on the same topic. Pages with higher information gain scores may be ranked higher than pages with lower scores, thus providing users with diverse and valuable information.
How Information Gain Scores are Calculated:
According to Slawski’s article, information gain scores can be determined by applying data indicative of pages, such as their entire contents or a semantic representation, across a machine learning model to generate an information gain score. This approach takes into account the information contained in previously-presented pages as well as yet-to-be presented pages, helping to generate an output indicative of the information gain score for new pages.
The Information Gain Score Process:
The process of calculating information gain scores and ranking search results based on them involves the following steps:
- Identifying the first set of pages displayed to the searcher.
- Identifying pages that share a common topic previously provided to the user.
- Determining an information gain score for each new page in the second set of pages, indicating whether that page includes information not contained in the pages of the first set of documents.
- Based on the information gain scores, selecting one or more new documents to provide to the user, and/or ranking the new documents based on their respective information scores.
- Re-ranking the new pages as the searcher views more pages, updating information gain scores accordingly.
The Impact on SEO:
The application of information gain scores can have a significant impact on SEO strategies. It may encourage content creators to focus on providing unique and valuable information to users instead of producing repetitive content that adds little value. This may lead to a more diverse range of high-quality content ranking higher in search results, ultimately benefiting both users and content creators.
Conclusion: No one likes copycats
Bill Slawski’s article on information gain scores highlights a significant development in Google’s search algorithms, emphasizing the importance of unique and valuable content. As a result, content creators should focus on providing new information to users and avoid repetitive content to improve their search rankings. By understanding and adapting to these changes, businesses and individuals can enhance their SEO strategies and achieve better results in the ever-competitive online space.
- Ranking Search Results based on Information Gain Scores
- Information Gain SEO
- How Google Search Organizes information – Constantly crawling for new information