Searching for authors named "Georgios Paliouras" – sorted by Relevance.
-
On the need to bootstrap ontology learning with extraction grammar learning
- Abstract. The main claim of this paper is that machine learning can help integrate the construction of ontologies and extraction grammars and lead us closer to the Semantic Web vision. The proposed approach is a bootstrapping process that combines ontology and grammar learning, in order to semi-auto
- Cited by 1 (0 self) – Add To MetaCart
-
Scalability Of Machine Learning Algorithms
- 10 The Author 13 Acknowledgements 15 1 Introduction 16 1.1 Definition of Learning : : : : : : : : : : : : : : : : : : : : : : : : 16 1.2 The objectives of ML : : : : : : : : : : : : : : : : : : : : : : : : : 17 1.3 Approaches taken so far : : : : : : : : : : : : : : : : : : : : : : : 18 1.4 Motivat
- Cited by 4 (1 self) – Add To MetaCart
-
Ion Androutsopoulos
- In the past few years, machine learning and in particular simple Naive Bayes classifiers have proven their value in filtering spam emails. We hereby put Naive Bayes filters to the test, against potentially more elaborate spam filters that will participate in the ceas 2008 challenge. For this purpose
- Add To MetaCart
-
Domain-specific web site identification: The crossmarc focused web crawler
- This paper presents techniques for identifying domain specific web sites that have been implemented as part of the EC-funded R&D project, CROSSMARC. The project aims to develop technology for extracting interesting information from domain-specific web pages. It is therefore important for CROSSMARC t
- Cited by 4 (3 self) – Add To MetaCart
-
The Effect of Numeric Features on the Scalability of Inductive Learning Programs
- The behaviour of a learning program as the quantity of data is increased affects to a large extent its applicability on real-world problems. This paper presents the results of a theoretical and experimental investigation of the scalability of four well-known empirical concept-learning programs. In p
- Cited by 1 (0 self) – Add To MetaCart
-
SHARE-ODS: An Ontology Data Service for Search and Rescue Operations
- This report describes an ontology data service (ODS) for supporting Search and Rescue (SaR) operations. The ontological model represents various aspects of the command, communication, and organisational structure of the SaR forces and the deployment and progress of a SaR operation. Furthermore, the
- Cited by 4 (3 self) – Add To MetaCart
-
Learning user communities for improving the services of information providers
- Abstract. In this paper we propose a methodology for organising the users of an information providing system into groups with common interests (communities). The communities are built using unsupervised learning techniques on data collected from the users (user models). We examine a system that filt
- Cited by 8 (2 self) – Add To MetaCart
-
Annotating Web pages for the needs of Web Information Extraction applications
- This paper outlines our approach to the creation of annotated corpora for the purposes of Web Information Extraction, and presents the Web Annotation tool. This tool enables the annotation of Web pages from different domains and for different information extraction tasks providing a user-friendly in
- Cited by 2 (2 self) – Add To MetaCart
-
A Methodology for Semantically Annotating a Corpus Using a Domain Ontology and Machine Learning
- In this paper we present a methodology for the semantic annotation of domain-specific corpora.
- Cited by 7 (2 self) – Add To MetaCart
-
Filtron: A Learning-Based Anti-Spam Filter
- We present Filtron, a prototype anti-spam filter that integrates the main empirical conclusions of our comprehensive analysis on using machine learning to construct e#ective personalized anti-spam filters. Filtron is based on the experimental results over several design parameters on four publicl
- Cited by 11 (2 self) – Add To MetaCart

