We propose a new method for mining frequent patterns in a language that combines both
Semantic Web ontologies and rules. In particular, we consider the setting of using a …

The authors propose a new method for mining sets of patterns for classification, where
patterns are represented as SPARQL queries over RDFS. The method contributes to so …

The architecture of an automatically tuned linear algebra library proposed in previous works
is extended in order to adapt itself to platforms where both the CPU load and the network …

Linked data (LD) is a rich format increasingly exploited in knowledge discovery from data
(KDD). To that end, LD is typically structured as graph, but can also fit the multi-relational …

À une époque où les données, souvent interprétées comme une «réalité terrain», sont
produites dans des quantités gargantuesques, un besoin de compréhension et …

Over the last two decades frequent itemset and association rule mining has attracted huge
attention from the scientific community which resulted in numerous publications, models …

The paper proposes the framework for clustering results of queries submitted over Semantic
Web data. As an instantiation of a framework, an approach is proposed for clustering the …

This chapter discusses about the veracity of data. The veracity issue is the challenge of
imprecision in big data due to influx of data from diverse sources. To overcome this problem …

As one of the fundamental data mining methods, the association rule mining has widely
been used in many fields. However, the existence of massive redundant rules has made the …

为发现语义Web 使用记录中所蕴含的有效信息, 本文提出了一种挖掘日志本体频繁Web
访问模式的方法. 该方法引入应用访问规则集和观察集分别表示日志信息动态变化的语义规则和 …