Novel Event Detection and Classification for Historical Texts

Temporal classification for historical Romanian texts

In this paper we look at a task at border of natural language processing, historical linguistics and the study of language development, namely that of identifying the time when a text was written. We use machine learning classification using lexical, word ending and dictionary-based features, with linear support vector machines and random forests. We find that lexical features are the most help...

Acoustic Event Detection and Classification

Classification Models for New Event Detection

New event detection (NED) involves monitoring news streams to detect the stories that report on new events. In this paper we explore the application of machine learning classification techniques for this task. We introduce the concept of triangulation with illustrative examples. We develop new features that build on this concept, and the named entities present in a document. The classifiers we ...

Bayesian Event Classification for Intrusion Detection

Intrusion detection systems (IDSs) attempt to identify attacks by comparing collected data to predefined signatures known to be malicious (misuse-based IDSs) or to a model of legal behavior (anomaly-based IDSs). Anomaly-based approaches have the advantage of being able to detect previously unknown attacks, but they suffer from the difficulty of building robust models of acceptable behavior whic...

Creating a Novel Geolocation Corpus from Historical Texts

This paper describes the process of annotating a historical US civil war corpus with geographic reference. Reference annotations are given at two different textual scales: individual place names and documents. This is the first published corpus of its kind in document-level geolocation, and it has over 10,000 disambiguated toponyms, double the amount of any prior toponym corpus. We outline many...