Locality-Constrained Concept Factorization

Liu, Haifeng; Yang, Zheng; Wu, Zhaohui

doi:10.5591/978-1-57735-516-8/IJCAI11-233

Locality-Constrained Concept Factorization

Haifeng Liu, Zheng Yang, Zhaohui Wu

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1378-1382.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-233

Abstract

Matrix factorization based techniques, such as nonnegative matrix factorization (NMF) and concept factorization (CF), have attracted great attention in dimension reduction and data clustering. Both of them are linear learning problems and lead to a sparse representation of the data. However, the sparsity obtained by these methods does not always satisfy locality conditions, thus the obtained data representation is not the best. This paper introduces a locality-constrained concept factorization method which imposes a locality constraint onto the traditional concept factorization. By requiring the concepts (basis vectors) to be as close to the original data points as possible, each data can be represented by a linear combination of only a few basis concepts. Thus our method is able to achieve sparsity and locality at the same time. We demonstrate the effectiveness of this novel algorithm through a set of evaluations on real world applications.

Haifeng Liu, Zheng Yang, and Zhaohui Wu. 2011. Locality-Constrained Concept Factorization. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 1378–1382. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-233

@inproceedings{ijcai2011p233,
  title     = {Locality-Constrained Concept Factorization},
  author    = {Liu, Haifeng and Yang, Zheng and Wu, Zhaohui},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {1378--1382},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-233},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-233},
}

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TI  - Locality-Constrained Concept Factorization
AU  - Liu, Haifeng
AU  - Yang, Zheng
AU  - Wu, Zhaohui
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 1378
EP  - 1382
DO  - 10.5591/978-1-57735-516-8/IJCAI11-233
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-233
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