Managing large collections of data mining models

Building and Querying Large Collections of Data Mining Models

Model building is one of the most important objectives of data mining and data analysis. As many statistical and data mining applications, such as personalization, bioinformatics and some large enterprise-wide business applications, become increasingly complex and require a very large number of models, it is becoming progressively more difficult for data analysts to built and to manage a large ...

Managing Large Collections

Model building is a key objective of data mining and data analysis applications. In the past, such applications required only a few models built by a single data analyst. As more and more data has been collected and realworld problems have become more complex, it has become increasingly difficult for that data analyst to build all the required models and manage them manually. Building a system ...

Data mining in large audio collections of dolphin signals

Managing and Mining Graph Data Managing and Mining Graph Data

Graph mining and management has become an important topic of research recently because of numerous applications to a wide variety of data mining problems in computational biology, chemical data analysis, drug discovery and communication networking. Traditional data mining and management algorithms such as clustering, classification, frequent pattern mining and indexing have now been extended to...

Managing and Mining Uncertain Data Managing and Mining Uncertain Data

In recent years, uncertain data has become ubiquitous because of new technologies for collecting data which can only measure and collect the data in an imprecise way. Furthermore, many technologies such as privacy-preserving data mining create data which is inherently uncertain in nature. As a result there is a need for tools and techniques for mining and managing uncertain data. This chapter d...