An XML Based Environment in Support of the Overall KDD Process

Alcamo, Piero; Domenichini, F.; Turini, Franco

doi:10.1007/978-3-7908-1834-5_38

Cited by 9 publications

(3 citation statements)

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“…A similar set of functionalities, i.e. the application of XML to the deployment of the KDD process, is available also in [1] while [3] provides a framework for extracting knowledge from XML documents. XDM, however, provides a set of features that is peculiar to the integration of different patterns and models in inductive databases.…”

Section: Introductionmentioning

confidence: 99%

An XML-Based Database for Knowledge Discovery

Meo

Psaila

2006

Current Trends in Database Technology – EDBT 2006

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Pattern Management Systems and Inductive Databases, are proposed as a new generation of general purpose databases with the aim to manage data mining patterns and work as knowledge bases in support to the deployment of the KDD process. One of the main problems to be solved is the integration between data and patterns and pattern maintenance when data update. Unfortunately, the heterogeneity of the patterns that represent the extracted knowledge and of the different conceptual tools used to find the patterns make difficult this integration in a unique framework. In this paper, we explore the feasibility of using XML as the unifying framework for inductive databases, and present a model, named XDM (XML for Data Mining). We will show the basic features of the model, such as the storage in the same database of both data and patterns. To store patterns, we consider determinant for their interpretation the storage of the pattern derivation process which is described by the concept of statement, based on data mining operators. Some of the statements are automatically generated by the system while maintaining consistence between source and derived data. Furthermore, we show how the use of XML namespaces allows the effective coexistence of different data mining operators and provides extensibility to new operators. Finally, we show that with the use of XML-Schema we are able to define the schema, the state and the integrity constraints of an inductive database.

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Section: Introductionmentioning

confidence: 99%

An XML-Based Database for Knowledge Discovery

Meo

Psaila

2006

Current Trends in Database Technology – EDBT 2006

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“…A partial solution to this problem has been proposed in [5,14,2]. In these approaches, data mining algorithms are modeled as "black boxes" integrated within the system.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study

Giannotti

Manco

Turini

2001

Principles of Data Mining and Knowledge Discovery

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We present a way of exploiting domain knowledge in the design and implementation of data mining algorithms, with special attention to frequent patterns discovery, within a deductive framework. In our framework domain knowledge is represented by deductive rules, and data mining algorithms are constructed by means of iterative userdefined aggregates. Iterative user-defined aggregates have a fixed scheme that allows the modularization of data mining algorithms, thus providing a way to exploit domain knowledge in the right point. As a case study, the paper presents user-defined aggregates for specifying a version of the apriori algorithm. Some performance analyses and comparisons are discussed in order to show the effectiveness of the approach.

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“…the application of XML to the deployment of the KDD process, is available also in [1] while [3] provides a framework for extracting knowledge from XML documents. XDM, however, provides a set of features that is peculiar to the integration of different patterns and models in inductive databases.…”

Section: Introductionmentioning

confidence: 99%

An XML-Based Database for Knowledge Discovery

Meo

Psaila

Intelligent Databases

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Abstract. Pattern Management Systems and Inductive Databases, are proposed as a new generation of general purpose databases with the aim to manage data mining patterns and work as knowledge bases in support to the deployment of the KDD process. One of the main problems to be solved is the integration between data and patterns and pattern maintenance when data update. Unfortunately, the heterogeneity of the patterns that represent the extracted knowledge and of the different conceptual tools used to find the patterns make difficult this integration in a unique framework.In this paper, we explore the feasibility of using XML as the unifying framework for inductive databases, and present a model, named XDM (XML for Data Mining). We will show the basic features of the model, such as the storage in the same database of both data and patterns. To store patterns, we consider determinant for their interpretation the storage of the pattern derivation process which is described by the concept of statement, based on data mining operators. Some of the statements are automatically generated by the system while maintaining consistence between source and derived data. Furthermore, we show how the use of XML namespaces allows the effective coexistence of different data mining operators and provides extensibility to new operators. Finally, we show that with the use of XML-Schema we are able to define the schema, the state and the integrity constraints of an inductive database.

show abstract

An XML Based Environment in Support of the Overall KDD Process

Cited by 9 publications

References 1 publication

An XML-Based Database for Knowledge Discovery

An XML-Based Database for Knowledge Discovery

Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study

An XML-Based Database for Knowledge Discovery

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