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Approximation to expected support of frequent itemsets in mining probabilistic sets of uncertain data
(Elsevier, 2015)
Knowledge discovery and data mining generally discovers implicit, previously unknown, and useful knowledge from data. As one of the popular knowledge discovery and data mining tasks, frequent itemset mining, in particular, ...
Edge-based mining of frequent subgraphs from graph streams
(Elsevier, 2015)
In the current era of Big data, high volumes of valuable data can be generated at a high velocity from high-varieties of data sources in various real-life applications ranging from sensor networks to social networks, from ...
Frequent subgraph mining from streams of linked graph structured data
(CEUR Workshop Proceedings, 2015)
Nowadays, high volumes of high-value data (e.g., semantic web data) can be generated and published at a high velocity. A collection of these data can be viewed as a big, interlinked, dynamic graph structure of linked ...
Effectively and efficiently mining frequent patterns from dense graph streams on disk
(Elsevier, 2014)
In this paper, we focus on dense graph streams, which can be generated in various applications ranging from sensor networks to social networks, from bio-informatics to chemical informatics. We also investigate the problem ...
Mining of diverse social entities from linked data
(CEUR Workshop Proceedings, 2014)
Nowadays, high volumes of valuable data can be easily generated or collected from various data sources at high velocity. As these data are often related or linked, they form a web of linked data. Examples include semantic ...
Frequent pattern mining from dense graph streams
(CEUR Workshop Proceedings, 2014)
As technology advances, streams of data can be produced in many applications such as social networks, sensor networks, bioinformatics, and chemical informatics. These kinds of streaming data share a property in common--namely, ...
A tree-based algorithm for mining diverse social entities
(Elsevier, 2014)
DiSE-growth, a tree-based (pattern-growth) algorithm for mining DIverse Social Entities, is proposed and experimentally assessed in this paper. The algorithm makes use of a specialized data structure, called DiSE-tree, for ...
Frequent itemset mining of distributed uncertain data under user-defined constraints
(Edizioni Libreria Progetto, 2012)
Many existing distributed data mining algorithms do not allow users to express the patterns to be mined according to their intention via the use of constraints. Consequently, these unconstrained mining algorithms can yield ...
Knowledge discovery from social graph data
(Elsevier, 2016)
High volumes of a wide variety of valuable data can be easily collected and generated from a broad range of data sources of different veracities at a high velocity. In the current era of big data, many traditional data ...
A combined deep-learning and transfer-learning approach for supporting social influence prediction
(Elsevier, 2020)
Social influence is a phenomenon describing the spread of opinions across the population. Nowadays, social influence analysis (SIA) has a great impact. For example, viral marketing and online content recommendation are ...