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Transfer learning over big data | IEEE Conference Publication | IEEE Xplore

Transfer learning over big data


Abstract:

Transfer learning has emerged as a new learning technique facilitating an improved learning result of one task by integrating the well learnt knowledge from another relat...Show More

Abstract:

Transfer learning has emerged as a new learning technique facilitating an improved learning result of one task by integrating the well learnt knowledge from another related task. While much research has been devoted to develop the transfer learning algorithms in the field of long text analysis, the development of the transfer learning techniques over the short texts still remains challenging. The challenge of short text data analysis arises due to its sparse nature, noise words, syntactical structure and colloquial terminologies used. In this paper, we propose AutoTL(Automatic Transfer Learning), a transfer learning framework in short text analysis with automatic training data selection and no requirement of data priori probability distribution. In addition, AutoTL enables an accurate and effective learning by transferring the knowledge automatically learnt from the online information. Our experimental results confirm the effectiveness and efficiency of our proposed technique.
Date of Conference: 21-23 October 2015
Date Added to IEEE Xplore: 14 January 2016
ISBN Information:
Conference Location: Jeju, Korea (South)

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