Lars E. Holzman

Learn More
One of the brain's most basic functions is integrating sensory data from diverse sources. This ability causes us to question whether the neural system is computationally capable of intelligently integrating data, not only when sources have known, fixed relative dependencies but also when it must determine such relative weightings based on dynamic(More)
This article reports our progress in the classification of expressions of emotion in network-based chat conversations. Emotion detection of this nature is currently an active area of research [8] [9]. We detail a linguistic approach to the tagging of chat conversation with appropriate emotion tags. In our approach, textual chat messages are automatically(More)
Few tools exist that address the challenges facing researchers in the Textual Data Mining (TDM) field. Some are too specific to their application, or are prototypes not suitable for general use. More general tools often are not capable of processing large volumes of data. We have created a Textual Data Mining Infrastructure (TMI) that incorporates both(More)
In this article we present a supervised learning algorithm for the discovery of finite state automata in the form of regular expressions in textual data. The automata generate languages that consist of various representations of features useful in information extraction. We have successfully applied this learning technique in the extraction of textual(More)
  • 1