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Template Induction over Unstructured Email Corpora

Related publications (36)

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Discourse-level features for statistical machine translation

Thomas Meyer

Machine Translation (MT) has progressed tremendously in the past two decades. The rule-based and interlingua approaches have been superseded by statistical models, which learn the most likely translations from large parallel corpora. System design does not ...

EPFL2015

Discourse-level Features for Statistical Machine Translation

Thomas Meyer

École Polytechnique Fédérale de Lausanne (EPFL)2014

Arabic Entity Graph Extraction Using Morphology, Finite State Machines, and Graph Transformations

Hamza Harkous

Research on automatic recognition of named entities from Arabic text uses techniques that work well for the Latin based languages such as local grammars, statistical learning models, pattern matching, and rule-based techniques. These techniques boost their ...

2012

An Agent-Based Focused Crawling Framework for Topic- and Genre-Related Web Document Discovery

Nikolaos Pappas

The discovery of web documents about certain topics is an important task for web-based applications including web document retrieval, opinion mining and knowledge extraction. In this paper, we propose an agent-based focused crawling framework able to retri ...

IEEE2012

Implicit Human Centered Tagging

Nicolae Suditu, Alessandro Vinciarelli

This paper provides a general introduction to the concept of Implicit Human-Centered Tagging (IHCT) - the automatic extraction of tags from nonverbal behavioral feedback of media users. The main idea behind IHCT is that nonverbal behaviors displayed when i ...

2009

Artificial immune system for the Internet

Slavisa Sarafijanovic

We investigate the usability of the Artificial Immune Systems (AIS) approach for solving selected problems in computer networks. Artificial immune systems are created by using the concepts and algorithms inspired by the theory of how the Human Immune Syste ...

EPFL2008

Resolving FP-TP Conflict in Digest-Based Collaborative Spam Detection by Use of Negative Selection Algorithm

Jean-Yves Le Boudec, Slavisa Sarafijanovic

A well-known approach for collaborative spam filtering is to determine which emails belong to the same bulk, e.g. by exploiting their content similarity. This allows, after observing an initial portion of a bulk, for the bulkiness scores to be assigned to ...

2008

Artificial Immune System For Collaborative Spam Filtering

Jean-Yves Le Boudec, Slavisa Sarafijanovic

Artificial immune systems (AIS) use the concepts and algorithms inspired by the theory of how the human immune system works. This document presents the design and initial evaluation of a new artificial immune system for collaborative spam filtering. Collab ...

Springer Verlag2008

Improving Digest-Based Collaborative Spam Detection

Jean-Yves Le Boudec, Slavisa Sarafijanovic

Spam is usually sent in bulk. A bulk mailing consists of many copies of the same original spam message, each sent to a different recipient. The copies are usually obfuscated, i.e. modified a bit in order to look different from each other. In collaborative ...

2008

Machine learning for information retrieval

David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...

EPFL2008