Zhe Wang will present his preFPO on Friday May 27 at 2PM in Room 402. The members of his committee are: Kai Li, advisor; Moses Charikar and Olga Troyanskaya, readers; Jennifer Rexford and Andrea LaPaugh; nonreaders. Everyone is invited to attend his talk. His abstract follows below. -------------------------- Title: Designing similarity search systems for multimodal data As images, videos and all kinds of non-text sensory data have taken the majority of the storage space, how to efficiently index and search them becomes an issue. The query by example kind of content based search method has become more popular and often can be used to compliment the existing search method. We have designed multiple search system to demonstrate the content based search capability and would discuss our experience about building such systems. First we describe VFerret system where we combine the image visual feature with audio features for personal video search. Second, we explore different aggregation methods to aggregate results from multiple features in a system to detect image spam emails. In the last system, we design a new method to combine image similarity search with product navigation to help user to find desired product in the product category tree. One of the common problem for the similarity search system is the space utilization for the feature vectors used to represent objects. Our group had developed sketch as a compact data structure to alleviate such problem. In order to use the sketch effectively, I have worked out a method to model the sketch and predict the best parameters to use given a sample dataset. Our experience in integrating the similarity search capability into different kinds of system show that the content based search can be an effective method to enhance the existing systems. By creatively exploit multiple modality from the data, we demonstrate much better performance than the traditional systems.