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Article
Nitrogen and Phosphorus Additions Impact Stability of Soil Organic Carbon and Nitrogen in Subtropical Evergreen Broad-Leaved Forest
Atmospheric nitrogen (N) deposition can have a series of effects on forest ecosystems. As N deposition increases N availability in forest ecosystems, soil phosphorus (P) becomes a limiting factor for forest pr...
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Chapter and Conference Paper
Causal Transfer Evidential Clustering
Classical prototype-based clustering algorithms usually cannot achieve satisfactory results when the data is insufficient. Transfer learning can be adopted to address this problem. For instance, in the recentl...
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Chapter and Conference Paper
Credal Clustering for Imbalanced Data
Traditional evidential clustering tends to build clusters where the number of data for each cluster fairly close to each other. However, it may not be suitable for imbalanced data. This paper proposes a new me...
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Chapter and Conference Paper
Evidential Clustering Based on Transfer Learning
Clustering is an essential part of data mining, which can be used to organize data into sensible groups. Among the various clustering algorithms, the prototype-based methods have been most popularly applied du...
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Chapter and Conference Paper
Fast Unfolding of Credal Partitions in Evidential Clustering
Evidential clustering, based on the notion of credal partition, has been successfully applied in many fields, reflecting its broad appeal and usefulness as one of the steps in exploratory data analysis. However, ...
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Chapter and Conference Paper
Evidential Weighted Multi-view Clustering
Generally, the data to be clustered are from one single view. In real clustering applications, sometimes the data are insufficient so that it is difficult to learn an ideal cluster model. In such cases, multi-...
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Chapter and Conference Paper
Evidential Community Detection Based on Density Peaks
Credal partitions in the framework of belief functions can give us a better understanding of the analyzed data set. In order to find credal community structure in graph data sets, in this paper, we propose a n...
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Chapter and Conference Paper
Semi-supervised Evidential Label Propagation Algorithm for Graph Data
In the task of community detection, there often exists some useful prior information. In this paper, a Semi-supervised clustering approach using a new Evidential Label Propagation strategy (SELP) is proposed t...
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Chapter and Conference Paper
Evidential Communities for Complex Networks
Community detection is of great importance for understanding graph structure in social networks. The communities in real-world networks are often overlapped, i.e. some nodes may be a member of multiple clusters. ...
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Chapter and Conference Paper
Evidential-EM Algorithm Applied to Progressively Censored Observations
Evidential-EM (E2M) algorithm is an effective approach for computing maximum likelihood estimations under finite mixture models, especially when there is uncertain information about data. In this paper we pres...
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Chapter and Conference Paper
Belief Hierarchical Clustering
In the data mining field many clustering methods have been proposed, yet standard versions do not take into account uncertain databases. This paper deals with a new approach to cluster uncertain data by using ...
