A few months ago we provided a behind the scenes look into how Bing is improving image search quality. In this post we wanted to take the opportunity to further that discussion highlighting some recent outreach we did with researchers to explore new approaches to improving image search quality. My colleague Eason Wang will give you a closer look at how we are taking advantage of Deep Learning and entity understanding to deliver more relevant...
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Search Quality Insights - Page 7
In this post we wanted to take the opportunity to give you a behind the scenes look at the ongoing work we are doing to improve image search quality at Bing. This blog will give you an overview of the many years of work done in Bing Research and Development in collaboration with Microsoft Research in our quest to deliver the most relevant images possible. My colleague Meenaz Merchant will give you a closer look at our approach and how that...
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Experimenting at large scale is fundamental for improving Bing. Last June, we published a blog in this Search Quality Insights series titled Experimentation and Continuous Improvement at Bing, which covered a specific type of experiments known as interleaving. In this blog, Dr. Ronny Kohavi describes our broader online experimentation efforts at large scale and includes compelling examples that illustrate the power of these efforts, e.g., he shows...
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The internet’s massive reach and ever growing accessibility makes it an attractive place for cyber-criminals, who use it to distribute malware to unsuspecting users. To deliver malicious software to the user at large scale, savvy hackers increasingly try to game search engines to amplify the effect of their exploits by targeting frequently visited sites. At Bing our job is to not only deliver relevant results, but also provide a safe...
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One technical problem in Web search is how best to measure the quality of search results. Our powerful machine learning systems correct the spelling of your query, interpret your search intent, differentiate quality pages from junk, rank documents from our index of tens of billions of documents, and optimize whole-page layout. These systems, and many more, must all be optimized towards user satisfaction. The problem is that there is no perfect...
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Most search engines still provide a fixed number of web links on the search results page, typically 10 blue links in addition to instant answers. But are 10 blue links the right number of links for all queries and scenarios? Intuitively it doesn’t seem so. For example, showing fewer search results in navigational queries may enable users get to their desired URL faster. Also, users may benefit from seeing more blue links when they return to...
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Autosuggest enables people to select a query from a pull-down menu of suggestions when they start typing a query. You often find the query you want in the menu and select it, saving you extra keystrokes while reducing a chance of misspelling. It is a feature that people may take for granted but upon examination it involves a tremendous amount of technical sophistication and computational horsepower. In this blog Antonio Gulli who is our...
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Is it Swarzinegar, Swarneger, Scwarznagger or Schwartiznegar? These are just a few of more than 2,000 different ways users on Bing have typed their queries in hope of searching for “Schwarzenegger.” The aim of the Bing Speller is to correct these queries so users receive relevant web results that match their intent even when their query is misspelt. A great speller makes a search engine feel like magic to the users. In this blog my...
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As I mentioned in my original post there has never been a more exciting or challenging time to be in the search space. The core to a great search engine has been and will always remain the same: delivering relevant, comprehensive and unbiased results that people can trust. We use thousands of signals from queries to documents and user feedback to determine the best search results and in turn make hundreds of improvements to our features every year...
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Back in March, Jan Pedersen explored the topic of Whole Page Relevance. In the post, he outlined how Bing ranks media objects to deliver a rich set of results that go beyond just web pages using machine learning techniques. These objects include videos, images, maps, news items and assorted media objects or what we call answers. Today, Kieran McDonald will detail how we ensure that the answers are not defective and the results match the intent of...
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