• N.V.Ramireddy
• P.M.Harish
• P.Aravind kumar
• A.Ravindra chowdary
• P.BhanuPrasad

Approximate Nearest neighbor (ANN) look has made incredible progress in numerous errands. In this paper, we address the issue by building up an online item quantization (online PQ) show and steadily refreshing the quantization codebook that obliges to the approaching spilling information. Additionally, to additionally reduce the issue of huge scale calculation for the online PQ refresh, we structure two spending requirements for the model to refresh halfway PQ codebook rather than all. We infer a misfortune bound which ensures the execution of our online PQ demonstrate. Moreover, we build up an online PQ show over a sliding window with the two information addition and erasure bolstered, to mirror the continuous conduct of the information. The examinations show that our online PQ display is both time-productive and viable for ANN look in powerful vast scale databases contrasted and benchmark techniques and the possibility of incomplete PQ codebook refresh further lessens the refresh cost.

MACHINE ACCESSIBLE PRODUCT QUANTIZATION IN VECTOR DIVISION

"MACHINE ACCESSIBLE PRODUCT QUANTIZATION IN VECTOR DIVISION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.11-14, February-2019, Available :http://www.jetir.org/papers/JETIR1902C03.pdf

"MACHINE ACCESSIBLE PRODUCT QUANTIZATION IN VECTOR DIVISION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp11-14, February-2019, Available at : http://www.jetir.org/papers/JETIR1902C03.pdf