Meet your users’ demand for more relevant, personalized content. Train your algorithm with high-quality data to increase user satisfaction
How we help
In an environment where users expect content to be personalized and relevant, you need to ensure that your algorithm is being trained on a regular basis with high-quality data sets. To scale to meet the demands of a global user base, you also need experienced local users who can evaluate social media content with the right level of cultural understanding. Appen provides the right resources to enhance your social media platform, based on your unique needs.
Whether it’s providing in-market resources to evaluate their own feeds or determining relevance through social connections, we work directly with every client to help address their specific business challenges. Once we have a clear understanding of your project goals, we design and launch a tailored program to fit your needs. Our seasoned project managers are an extension of your team, and can quickly ramp the necessary resources to start generating results right away.
With over 20 years of industry experience, Appen works with leaders in the social media industry to improve their platforms for users worldwide. We have access to an experienced global crowd of over 1 million people, allowing us to quickly ramp new projects 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.
- Content Moderation
Scale your content moderation efforts using local experts for product reviews, site content and more.
- Field Testing
Ensure a successful launch of your application or system by using local testers in the field
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 …
Insights from AI NextCon 2018: How LinkedIn Uses AI to Optimize the User Experience
When it comes to building its AI platform, the LinkedIn team’s goal has been to make end-to-end machine learning easy, fast, robust and automatic.
Improving Local Search Results for Enhanced User Experience [Case Study]
When a search engine provider needed to keep up with business listing demand, it turned to Appen to ensure accuracy.