8 Result(s)
within
Data Mining and Knowledge Discovery
Dong** Lu
Chapter
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Chapter and Conference Paper
Exploiting Semantic Hierarchies for Flickr Group
The development of Web 2.0 provides a convenient platform for on-line members to exchange information, keep contact with others and express oneselves. Flickr group, as a representative one, is a user-organized...
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Chapter and Conference Paper
A Technique for Improving the Performance of Naive Bayes Text Classification
Naive Bayes classifier is widely used in text classification tasks, and it can perform surprisingly well, it is often regarded as a baseline. But previous researches show that the skewed distribution of traini...
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Chapter and Conference Paper
A Novel Approach to Image Assessment by Seeking Unification of Subjective and Objective Criteria Based on Supervised Learning
Image quality assessment is a challenge research topic in imaging engineering and applications, especially in the case where the reference image cannot be accessed, such as aerial images. In view of such an is...
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Chapter and Conference Paper
Improving Semi-supervised Text Classification by Using Wikipedia Knowledge
Semi-supervised text classification uses both labeled and unlabeled data to construct classifiers. The key issue is how to utilize the unlabeled data. Clustering based classification method outperforms other s...
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Chapter and Conference Paper
OptRegion: Finding Optimal Region for Bichromatic Reverse Nearest Neighbors
The MaxBRNN problem is to find an optimal region such that setting up a new service site within this region might attract the maximal number of customers by proximity. It has many practical applications such a...
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Chapter and Conference Paper
Finding Frequent Items in Time Decayed Data Streams
Identifying frequently occurring items is a basic building block in many data stream applications. A great deal of work for efficiently identifying frequent items has been studied on the landmark and sliding w...
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Chapter and Conference Paper
Topology of Surface Displacement Shape Feature in Subcortical Structures
The shape of anatomical structures in the brain has been adversely influenced by neurodegenerative disorders. However, the shape feature covariation between regions (e.g. subfields) of the structure and its ch...
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Chapter and Conference Paper
Learning Local Feature Descriptors with Quadruplet Ranking Loss
In this work, we propose a novel deep convolutional neural network (CNN) with quadruplet ranking loss to learn local feature descriptors. The proposed model receives quadruplets of two corresponding patches an...
