Bing Search Relevance and Index Quality

Bing Search Relevance Data Auditing is a project that its main purpose is to ensure the relevance data quality is good so that it can be useful for machine learning and further improve Bing's relevance. 

My Role and Works

Bing China/Japan Relevance NDCG

​I was responsible for the NDCG score of the Bing CN and JP market. To make sure the score is good every week, I led a team to review Bing's relevance data on a weekly basis and find out which scenario (such as freshness, relevance, authority, etc) Bing still needs to improve. 

​I was also responsible for optimizing the guideline of relevance measurement, communication with data auditors across the globe (mostly UK, US, Brazil) to discuss each market's performance and solution to solve problems we were facing as well as training and managing offsite vendors. 


Bing China/Japan Index Quality

​I was responsible for the Index data quality of the Bing CN and JP market. I led a team to review Bing's index data on a weekly basis and find out new categories and websites of either spam or junk websites within Bing's index. 

To make that happen, I was also responsible for updating the Index Quality guideline for Bing Spam and Junk categories. Once updated majorly, I also need to doing training for PMs and Devs to keep eveyrone on the same page. 

Bing Data Projects

During my 2 years of work at Bing. I was also in charge of more than 60 ad hoc data projects. Each data project is usually different from the others and have different goals. Things I need to consider for each project include: Requirement, project goal, project budget, ETA, guideline, vendor resource, vendor training, raw data quality, labeled data quality, review quality and delivery.