The use of non-linear data structures is becoming more and more common in many data
mining scenarios. Trees, in particular, have drawn the attention of researchers as the …

This chapter describes a principled approach to meta-learning that has three distinctive
features. First, whereas most previous work on meta-learning focused exclusively on the …

Knowledge Discovery in Databases is a complex process that involves many different data
processing and learning operators. Today's Knowledge Discovery Support Systems can …

为更好地共享与复用工程知识, 提出一种将情境特征作为共享与复用基础的知识检索技术.
在该技术中, 知识的情境特征被表示为分层和树状模型, 每一种工程知识都关联具体的情境树 …

Frequent closed pattern discovery is one of the most important topics in the studies of the
compact representation for data mining. In this paper, we consider the frequent closed …

Data mining (DM) can be an extremely complex process in which the data analyst has to
assemble into a DM workflow a number of data preprocessing and data mining operators in …

ABSTRACT A graph is a basic data structure which, can be used to model complex
structures and the relationships between them, such as XML documents, social networks …

Predictive graph mining approaches in chemical databases are extremely popular and
effective. Most of these approaches first extract frequent sub-graphs and then use them as …

Various definitions and frameworks for discovering frequent trees in forests have been
developed recently. At the heart of these frameworks lies the notion of matching, which …

Data that can conceptually be viewed as tree structures occurs extensively in domains such
as bio-informatics, web logs, XML databases and computer networks. One important …