NLP Advancements for Yahoo Search
Yahoo
The Challenge
Yahoo's search platform processes vast volumes of data across multiple languages for millions of users worldwide. Key challenges included interpreting incomplete or unclear search queries, understanding queries across diverse languages while maintaining accuracy, and legacy systems that couldn't efficiently handle massive advertising data volume.
The company needed to solve query ambiguity at scale, support multilingual data processing without sacrificing precision, and modernize its infrastructure for scalability.
Our Approach
We developed an advanced Named Entity Recognition (NER) system tailored to Yahoo's requirements. This unsupervised learning model leveraged Yahoo's extensive search log data to enhance query understanding and relevance.
Key innovations included unsupervised learning enabling adaptability across languages without labeled data, an enhanced search architecture seamlessly integrated with Yahoo's existing systems, and data-driven optimization leveraging petabytes of anonymized data.
Results
15%
Increase in search query relevance
80%
Of ambiguous searches optimized
30%
Reduction in manual intervention
Improved
User engagement through more accurate results
“Innovandio is a highly capable and reliable partner that applied a structured and analytical approach, backed by deep technical expertise, which led to outstanding project outcomes.”
Ricardo Baeza-Yates
VP of Research at Yahoo Labs
Technologies Used
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