A set of semantic relations is created every time a domain modeler wants to solve some complex problem computationally. These relations are usually organized into ontologies. But there is little standardization of ontologies today, and almost no discussion on ways of comparing relations, of determining a general approach to creating relations, or of modeling in general. This chapter outlines an...

Taxonomies are becoming essential in several fields, playing an important role in a large number of applications, particularly for specific domains. Taxonomies provide efficient tools to people by organizing a huge amount of information into a small hierarchical structure. Taxonomies were originally built by hand, but nowadays the technology permits to produce a vast amount of information. Cons...

Taxonomy construction provides an efficient navigating and browsing mechanism to people by organizing large amounts of information into a small number of hierarchical clusters. Compared with manually editing taxonomies, Automated Taxonomy Generation has numerous advantages and has therefore been applied to categorize document collections. However, the utility of this technique to organize and r...

We introduce EXTASEM!, a novel approach for the automatic learning of lexical taxonomies from domain terminologies. First, we exploit a very large semantic network to collect thousands of in-domain textual definitions. Second, we extract (hyponym, hypernym) pairs from each definition with a CRF-based algorithm trained on manually-validated data. Finally, we introduce a graph induction procedure...

We discuss how to classify input inductively where we assume taxonomy on attributes. Although we learn classi cation rules inductively by means of decision tree generation, we can't utilize the generation and testing methodologies for this purpose since each input data carries multiple roles based on taxonomy. In this investigation we introduce Decision Tree with Hierarchy (DTH) to class and at...

Classifiers like ANN & SVM are always preferred over other classification model like decision tree due to higher accuracy but lacking explainability and comprehensibility. Rule extraction techniques bridges gap between accuracy and comprehensibility. To evaluate and compare different rule extraction techniques, we require measures for evaluation and categorization. Taxonomy helps us to select a...

A intrusion provides an unauthorized access, damage or disruption of the network. The process can understand the characteristics and nature of an intruder. The paper presents the taxonomy consists of the specification of an intruder. Taxonomy provides the classification of intruder and provides mechanism for intruder detection. We found the algorithm for developing an intruder which can be atta...

The focus of this paper is the discovery of negative association rules. Such association rules are complementary to the sorts of association rules most often encountered in literatures and have the forms of X→¬Y or ¬X→Y. We present a rule discovery algorithm that finds a useful subset of valid negative rules. In generating negative rules, we employ a hierarchical graph-structured taxonomy of do...

In this study we address the problem of answering queries over information sources storing objects which are indexed by terms arranged in a taxonomy. We examine query languages of different expressivity and sources with different kinds of taxonomies. In the simplest kind, the taxonomy includes just term-to-term subsumption links. This case is used as a basis for further developments, in which w...