Data mining with unsupervised clustering using photonic micro-ring resonators

Alastair D. McAulay

doi:10.1117/12.2028381

Abstract

Data is commonly moved through optical fiber in modern data centers and may be stored optically. We propose an optical method of data mining for future data centers to enhance performance. For example, in clustering, a form of unsupervised learning, we propose that parameters corresponding to information in a database are converted from analog values to frequencies, as in the brain's neurons, where similar data will have close frequencies. We describe the Wilson-Cowan model for oscillating neurons. In optics we implement the frequencies with micro ring resonators. Due to the influence of weak coupling, a group of resonators will form clusters of similar frequencies that will indicate the desired parameters having close relations. Fewer clusters are formed as clustering proceeds, which allows the creation of a tree showing topics of importance and their relationships in the database. The tree can be used for instance to target advertising and for planning.

Citation Download Citation

Alastair D. McAulay, Alastair D. McAulay, "Data mining with unsupervised clustering using photonic micro-ring resonators", Proc. SPIE 8855, Optics and Photonics for Information Processing VII, 88550M (26 September 2013); doi: 10.1117/12.2028381; https://doi.org/10.1117/12.2028381

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