Triplex transfer learning: exploiting both shared and distinct concepts for text classification

Authors:
Fuzhen Zhuang;Ping Luo;Changying Du;Qing He;Zhongzhi Shi
Affiliations:
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Hewlett-Packard Labs, China, Beijing, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Venue:
Proceedings of the sixth ACM international conference on Web search and data mining
Year:
2013

Citing 24
Cited 0

Unsupervised learning by probabilistic latent semantic analysis

Machine Learning
Transductive Inference for Text Classification using Support Vector Machines

ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Orthogonal nonnegative matrix t-factorizations for clustering

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Boosting for transfer learning

Proceedings of the 24th international conference on Machine learning
Co-clustering based classification for out-of-domain documents

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A two-stage approach to domain adaptation for statistical classifiers

Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Knowledge transformation from word space to document space

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Topic-bridged PLSA for cross-domain text classification

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Knowledge transfer via multiple model local structure mapping

Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Transfer learning from multiple source domains via consensus regularization

Proceedings of the 17th ACM conference on Information and knowledge management
EigenTransfer: a unified framework for transfer learning

ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Heterogeneous source consensus learning via decision propagation and negotiation

Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Knowledge transformation for cross-domain sentiment classification

Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Transfer learning via dimensionality reduction

AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification

ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Multi-domain learning by confidence-weighted parameter combination

Machine Learning
Nonnegative shared subspace learning and its application to social media retrieval

Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A Survey on Transfer Learning

IEEE Transactions on Knowledge and Data Engineering
Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification

CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Multi-view transfer learning with a large margin approach

Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Feature selection for transfer learning

ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Bi-weighting domain adaptation for cross-language text classification

IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Domain Adaptation via Transfer Component Analysis

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

Transfer learning focuses on the learning scenarios when the test data from target domains and the training data from source domains are drawn from similar but different data distribution with respect to the raw features. Some recent studies argued that the high-level concepts (e.g. word clusters) can help model the data distribution difference, and thus are more appropriate for classification. Specifically, these methods assume that all the data domains have the same set of shared concepts, which are used as the bridge for knowledge transfer. However, besides these shared concepts each domain may have its own distinct concepts. To address this point, we propose a general transfer learning framework based on non-negative matrix tri-factorization which allows to explore both shared and distinct concepts among all the domains simultaneously. Since this model provides more flexibility in fitting the data it may lead to better classification accuracy. To solve the proposed optimization problem we develop an iterative algorithm and also theoretically analyze its convergence. Finally, extensive experiments show the significant superiority of our model over the baseline methods. In particular, we show that our method works much better in the more challenging tasks when distinct concepts may exist.