Train your search algorithm with the right data to give users more relevant search results
How we help
In an environment where users expect faster, more relevant search results, you need to ensure that your search algorithm is being trained on a regular basis with high-quality data sets. To scale to a global user base, you also need experienced local users who can evaluate query results with the right level of cultural understanding.
Appen can help. With years of experience helping to improve search algorithms for users worldwide, we can dramatically improve your search relevance and user satisfaction.
Whether your team is concerned with the accuracy of query results, ad performance or personalization, our team will design a program to address your specific business challenges. Further, our skilled global crowd provides access to over 130 target markets, allowing you to scale your search relevance efforts to meet global customer needs.
Our seasoned project managers are an extension of your team, and can quickly ramp the necessary resources to start generating results right away. Our team also works closely with you to ensure that quality levels meet your standards.
Through our years of experience improving search algorithms for clients worldwide, we’ve developed a strong and repeatable methodology for search relevance projects. And with access to an experienced crowd of over 1 million people worldwide, we can quickly scale to meet our customers’ needs.
Our data services
- Consultative Services
We work closely with your team to develop a customized program that addresses your unique business challenges.
- Data Annotation
Improve your machine learning-based products with high-quality, human-annotated training data.
Train your algorithm to deliver more personalized results for your users, driving higher satisfaction and engagement.
- Relevant Search Evaluation
We provide customized programs designed to improve the accuracy and relevancy of your search results.
- Semantic Annotation
Improve product listings and on site search with semantic annotation.
- Translation and Localization
Traditional translation and machine translation services from language and data experts.
Why Human-Annotated Data is Key to Machine Learning: Three Use Cases
Machine learning requires high volumes of data for training, validation, and testing. A machine learning model learns to find patterns in the input that is fed to it. This input is referred to as training data. As you train your solution to form relationships between variables, it’s important to have the right data, structured in the right format, covering all …