Bilkent University
Department of Computer Engineering


Diversity based Relevance Feedback for Time Series Search


Bahaddin Eravcı
PhD Student
Computer Engineering Department
Bilkent University

We propose a diversity based relevance feedback approach for time series data to improve the accuracy of search results. We ?rst develop the concept of relevance feedback for time series based on dual-tree complex wavelet (CWT) and SAX based approaches. We aim to enhance the search quality by incorporating diversity in the results presented to the user for feedback. We then propose a method which utilizes the representation type as part of the feedback, as opposed to a human choosing based on a preprocessing or training phase. The proposed methods utilize a weighting to handle the relevance feedback of important properties for both single and multiple representation cases. Our experiments on a large variety of time series data sets show that the proposed diversity based relevance feedback improves the retrieval performance. Results con?rm that representation feedback incorporates item diversity implicitly and achieves good performance even when using simple nearest neighbor as the retrieval method. To the best of our knowledge, this is the ?rst study on diversi?cation of time series search to improve retrieval accuracy and representation feedback. (Link:


DATE: 24 October, 2016, Monday @ 15:40