Identify a person from Iris Pattern using GLCM features and Machine Learning Techniques

Using Machine Learning Techniques to Identify Botnet Traffic

To date, techniques to counter cyber-attacks have predominantly been reactive; they focus on monitoring network traffic, detecting anomalies and cyber-attack traffic patterns, and, a posteriori, combating the cyber-attacks and mitigating their effects. Contrary to such approaches, we advocate proactively detecting and identifying botnets prior to their being used as part of a cyber-attack [12]....

Creating Glossaries Using Pattern-Based and Machine Learning Techniques

One of the aims of the Language Technology for eLearning project is to show that Natural Language Processing techniques can be employed to enhance the learning process. To this end, one of the functionalities that has been developed is a pattern-based glossary candidate detector which is capable of extracting definitions in eight languages. In order to improve the results obtained with the patt...

Iris recognition through machine learning techniques: A survey

Using Linguistic Information and Machine Learning Techniques to Identify Entities from Juridical Documents

Information extraction from legal documents is an important and open problem. A mixed approach, using linguistic information and machine learning techniques, is described in this paper. In this approach, top-level legal concepts are identified and used for document classification using Support Vector Machines. Named entities, such as, locations, organizations, dates, and document references, ar...

Using Machine Learning to Identify Intonational Segments

The intonational phrase is hypothesized to represent a meaningful unit of analysis in spoken language interpretation. We present results on the identification of intonational phrase boundaries from acoustic features using classification and regression trees (CART). Our training and test data are taken from the Boston Directions Corpus (task-oriented monologue) and the HUB-IV Broadcast News data...