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Dual instance and attribute weighting for Naive Bayes classification
Naive Bayes (NB) network is a popular classification technique for data mining and machine learning. Many methods exist to improve the …
DOI
Exploring features for complicated objects: cross-view feature selection for multi-instance learning
In traditional multi-instance learning (MIL), instances are typically represented by using a single feature view. As MIL becoming …
DOI
Multi-graph learning with positive and unlabeled bags
In this paper, we formulate a new multi-graph learning task with only positive and unlabeled bags, where labels are only available for …
DOI
Graph classification with imbalanced class distributions and noise
Recent years have witnessed an increasing number of applications involving data with structural dependency and graph representations. …
Graph stream classification using labeled and unlabeled graphs
Graph classification is becoming increasingly popular due to the rapidly rising applications involving data with structural dependency. …
DOI
CGStream: Continuous correlated graph query for data streams
In this paper, we propose to query correlated graph in a data stream scenario, where given a query graph q an algorithm is required to …
DOI
Continuous top-k query for graph streams
In this paper, we propose to query correlated graphs in a data stream scenario, where an algorithm is required to retrieve the top k …
DOI
Top-k correlated subgraph query for data streams
Given a query graph q, correlated subgraph query intends to find graph structures which are mostly correlated to the query q. This …
Classifier ensemble for uncertain data stream classification
Currently available algorithms for data stream classification are all designed to handle precise data, while data with uncertainty or …
DOI
Ensemble of multiple descriptors for automatic image annotation
Automatic image annotation (AIA) plays an important role and attracts much research attention in image understanding and retrieval. …
DOI