Specifying and Learning Inductive Learning Systems Using Ontologies

Inductive Learning for Rule Generation from Ontology

This paper presents an idea of inductive learning use for rule generation from ontologies. The main purpose of the paper is to evaluate the possibility of inductive learning use in rule generation from ontologies and to develop the way how this can be done. Generated rules are necessary to supplement or even to develop the Semantic Web Expert System (SWES) knowledge base. The SWES emerges as th...

CAMLET: A Platform for Automatic Composition of Inductive Learning Systems Using Ontologies

طراحی سامانه هوشمند ساخت هستان نگار به کمک شبکه عصبی ARTو روشC-value

In recent years, many efforts have been done to design ontology learning methods and automate ontology construction process. The ontology construction process is a time-consuming and costly procedure for almost all domains/applications, so automating this process is a solution to overcome the knowledge acquisition bottleneck in information systems and reduce the construction cost. In this artic...

Requirements for Machine Lifelong Learning

A significant advance in inductive modelling are systems that retain learned knowledge and selectively transfer portions of that knowledge as a source of inductive bias. We define such to be machine lifelong learning (ML3) systems. This paper makes an initial effort at specifying the scope of ML3 systems and their functional requirements.

تولید خودکار الگوهای نفوذ جدید با استفاده از طبقه‌بندهای تک کلاسی و روش‌های یادگیری استقرایی

In this paper, we propose an approach for automatic generation of novel intrusion signatures. This approach can be used in the signature-based Network Intrusion Detection Systems (NIDSs) and for the automation of the process of intrusion detection in these systems. In the proposed approach, first, by using several one-class classifiers, the profile of the normal network traffic is established. ...