Abstract
Distance-based indexing is a widely used technique for general purpose search. Pivot selection is the most crucial step of bulkloading a metric-space indexing tree. Current pivot selection methods are mainly based on linear methods. A non-linear method based on Locally Linear Embedding is proposed. Empirical results demonstrate that the performance of new method is superior to existing methods. Keywords-similarity search; metric-space indexing; pivot selection; locally linear embedding; dimensional reduction
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
