Master of Science (MS)
News Aggregation, Distributed Computing
The ability to display different media sources in an appropriate way is an integral part of search engines such as Google, Yahoo, and Bing, as well as social networking sites like Facebook, etc. This project explores and implements various media-updating features of the open source search engine Yioop . These include news aggregation, video conversion and email distribution. An older, preexisting news update feature of Yioop was modified and scaled so that it can work on many machines. We redesigned and modified the user interface associated with a distributed news updater feature in Yioop. This project also introduced a video updater feature for Yioop. This feature converts uploaded video into formats that are compatible with all browsers. It can quickly convert lengthy videos by splitting and converting them in a parallel fashion. It then merges them back into a single video. In this report, we discuss a solution to off- load the task of sending emails from the Yioop web application to the Yioop media updater by aggregating emails over a period of time. We conclude this report by describing experiments with these developed features on a cluster setup on an AWS platform.
Mishra, Pooja, "A SCALABLE SEARCH ENGINE AGGREGATOR" (2015). Master's Projects. 400.