Kvasir: Seamless Integration of Latent Semantic Analysis-Based Content Provision into Web Browsing

The Internet is overloading its users with excessive information flows, so that effective content-based filtering becomes crucial in improving user experience and work efficiency. We build Kvasir, a semantic recommendation system, atop latent semantic analysis and other state-of-art technologies to seamlessly integrate an automated and proactive content provision service into web browsing. We utilize the power of Apache Spark to scale up Kvasir to a practical Internet service. Herein we present the architecture of Kvasir, along with our solutions to the technical challenges in the actual system implementation.