Collaborative Filtering for IDEAL

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The students of CS5604 (Information Retrieval and Storage), have been building an Information Retrieval System based on tweet and webpage collections of the Digital Library Research Laboratory (DLRL). The students have been grouped into smaller teams such as Front End team, Solr team, and Collaborative Filtering team, which are building the individual subsystems of the entire project. The teams are collaborating among themselves to integrate their individual subsystems. The Collaborative Filtering (CF) team has been building a recommendation system that can recommend tweets and webpages to users based on content similarity of document pairs as well as user pair similarity. We have finished building the recommendation system so that when the user starts using the system they will be recommended to documents that are similar to those returned by their queries. As more users coming in, they will be also referred to documents that similar users were interested in.

There is a complete report describing our tasks, work and evaluation, slides that we used to present our project in class, and code implementation details.
information retrieval and storage, collaborative filtering, recommendation system