Categorization of process names

Incremental Recognition and Referential Categorization of French Proper Names

This paper presents Nemesis, a French proper name (PN) recognizer for Large-scale Information Extraction (IE), whose specifications have been elaborated through corpus investigation both in terms of referential categories and graphical structures. The graphical criteria are used to identify proper names and the referential classification to categorize them. The system is a classical one: it is ...

Improved Intrusive Process Detection Via Text Categorization

This paper compares the efficacy of two anomaly detection classifiers with respect to the classification of processes as either intrusive or non-intrusive. To the task of process classification, both classifiers treat processes as system call sequences, encode those system call sequences as text documents, and apply the k-nearest neighbor text categorization method to classify the processes. In...

Modeling Categorization as a Dirichlet Process Mixture

I describe an approach to modeling the dynamics of human category learning using a tool from nonparametric Bayesian statistics called the Dirichlet process mixture model (DPMM). The DPMM has a number of advantages over traditional models of categorization: it is interpretable as the optimal solution to the category learning problem, given certain assumptions about learners’ biases; it automatic...

Self-Categorization as a Social Process by

The Influence of Context during the Categorization and Discrimination of Spanish and Portuguese Person Names

This paper presents a method for fine-grained categorization and discrimination of person names on the basis of the semantic similarity information. We employ latent semantic analysis which establishes the semantic relations between the words of the context in which the named entities appear. We carry out several experimental studies in which we observe the influence of the context and the robu...