Improving Search Quality for Microsoft Bing in Multiple Markets

Published on

August 21, 2017

Author

Authors

Appen

No items found.

Developing Relevant Search Results

The Situation

Microsoft’s Bing search engine requires large-scale data sets to continuously deliver relevant search results – in all the global markets they serve.

The Solution

After an initial trial, Appen became an agile partner for Microsoft in multiple markets. Appen is able to provide the Bing team with the following:

An expert team of linguistic resources
Recommendations for improving the evaluation process
Millions of search query judgments every month in more than 12 markets worldwide
A proprietary data analysis and reporting tool to ensure consistency and efficiency

The Results

As a proactive partner, Appen has delivered results that have surpassed expectations. Beyond delivering project and program management, Appen provides:

The ability to grow rapidly in new markets
The delivery of high-quality data sets

What is Human-in-the-Loop Machine Learning?

Human-in-the-loop (HITL) is a branch of artificial intelligence that leverages both human and machine intelligence to create machine learning models. In a traditional

Deciphering AI from Human Generated Text: The Behavioral Approach

One of the most important elements of building a well-functioning AI model is consistent human feedback. When generative AI models are trained by human annotators, they serve

Data Quality: The Better the Data, the Better the Model

If your data’s not accurate, your model won’t run...properly, that is. While you may end up with a working model, it won’t function the way it was intended. The quality of

Machine Vision vs. Computer Vision — What’s the Difference?

Artificial Intelligence is an umbrella term that covers several specific technologies. In this post, we will explore machine vision (MV) vs. computer vision (CV). They both