| Title | Stacked K-Means Hashing Quantization for Nearest Neighbor Search |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Chen, Yalin, Li, Zhiyang, Shi, Jia, Liu, Zhaobin, Qu, Wenyu |
| Conference Name | 2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM) |
| Date Published | sep |
| Keywords | binary code optimizing, codes data, fast nearest neighbor search, high dimensional data, High-dimensional Vectors, higher-dimensional cubes, hypercube increases, improved hashing method, information available online, k-means, K-means Hashing, KMH divides, KMH method, low-dimensional subspaces, Measurement, mentioned optimizing process, Metrics, multilayer lower-dimensional cubes, nearest neighbor search, optimisation, optimizing time, pubcrawl, search problems, similar approximation ability, SKMH, stacked k-means hashing quantization, target data |
| Abstract | Nowadays, with such a huge amount of information available online, one key challenge is how to retrieve target data efficiently. A recent state-of-art solution, k-means hashing (KMH), codes data via a string of binary code obtained by iterative k-means clustering and binary code optimizing. To deal with high dimensional data, KMH divides the space into low-dimensional subspaces, places a hypercube in each subspace and finds its proper location by the mentioned optimizing process. However, the complexity of the optimization increases rapidly when the dimension of the hypercube increases. To address this issue, we propose an improved hashing method stacked k-means hashing (SKMH). The main idea is to increase the approximation by a coarse-to-fine multi-layer lower-dimensional cubes. With these kinds of lower-dimensional cubes, SKMH can achieve a similar approximation ability via a less optimizing time, compared with KMH method using higher-dimensional cubes. Extensive experiments have been conducted on two public databases, demonstrating the performance of our method by some common metrics in fast nearest neighbor search. |
| DOI | 10.1109/BigMM.2018.8499296 |
| Citation Key | chen_stacked_2018 |
Stacked K-Means Hashing Quantization for Nearest Neighbor Search