activity
20002007
most citedLearning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach

281 citations · 607 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2007★ 12 cited

Using Synchronic and Diachronic Relations for Summarizing Multiple Documents Describing Evolving Events

Stergos D. Afantenos, V. Karkaletsis, P. Stamatopoulos +1

In this paper we present a fresh look at the problem of summarizing evolving events from multiple sources. After a discussion concerning the nature of evolving events we introduce…

cs.CL2005★ 6 cited

Summarizing Reports on Evolving Events; Part I: Linear Evolution

Stergos D. Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos

We present an approach for summarization from multiple documents which report on events that evolve through time, taking into account the different document sources. We distinguish…

cs.CL2005★ 164 cited

Summarization from Medical Documents: A Survey

Stergos D. Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos

Objective: The aim of this paper is to survey the recent work in medical documents summarization. Background: During the last decade, documents summarization got increasing attenti…

cs.CL2001★ 144 cited

Stacking classifiers for anti-spam filtering of e-mail

G. Sakkis, I. Androutsopoulos, G. Paliouras +3

We evaluate empirically a scheme for combining classifiers, known as stacked generalization, in the context of anti-spam filtering, a novel cost-sensitive application of text categ…

cs.CL2000★ 281 cited

Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach

Ion Androutsopoulos, Georgios Paliouras, Vangelis Karkaletsis +3

We investigate the performance of two machine learning algorithms in the context of anti-spam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee…