Bing Search Quality & Scientific Research

Currently, the Internet has established a powerful presence in regards to finding information, specific images, or anything else in the interest of the user. Many people rely on search engines to help scour the web in a quick, efficient manner; without them, there would be too much information to sift through.

Not only does this apply to the general public, but also businesses as well, since they work on search engine optimization to help themselves be visible in search results. It is an obvious observation to say that search engines are a valued resource for anybody who uses the Internet extensively, and choosing the best search engine for quality results is important for any task.



Microsoft Research and Bing R&D understand how important it is to provide the best results to their users, so they have taken it upon themselves to make major contributions to the science of search quality. Their ideas come in the form of scientific articles and journals, which are usually accepted only when they have been reviewed by the community of search experts.

The ideas accepted are transformed into techniques used by Microsoft to enhance the capabilities of the Bing search engine. This cycle continues as they contribute their ideas to the research community devoted to enhancing how machines retrieve information.

To provide an example of the innovations being developed, filters for image searches have seen much improvement because how they are identified by machines. The specific technique is known as salient object detection, which looks for the primary component of the image: the salient object. To identify such a component, two stages occur to identify the existence of the salient object and then locate it on the image; this is done alongside a global description database to enhance the method of identification.


Bing Image search


Once found, the dominant color is extracted for filtering image searches. Such innovations are important in showing how enhancing vision and pattern recognition in machines is significant for search quality.

Both Microsoft and Bing R&D continue to be active in their contributions to the various communities and conferences held for the discussion of search-related topics like machine learning. Discussions and journals that impact the science of search result from these conferences; therefore, all research ideas represented are judged to be proven useful by the community as a whole.

Because of the significance the community holds, Microsoft stays active in providing papers and interacting with them. From information retrieval to human-computer interactions, their publications have shown their leadership in the scientific research of search quality.

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