When applying association mining to real datasets, a major obstacle is that often a huge number of rules are generated even with very reasonable support and confidence. Among thes...
Ping Chen, Rakesh M. Verma, Janet C. Meininger, We...
We address the problem of computing an optimal value function for Markov decision processes. Since finding this function quickly and accurately requires substantial computation ef...
This paper describes a heuristics-based system for automatic measurement of syntactic complexity using the revised Developmental Level (D-Level) Scale (Rosenberg and Abbeduto, 198...
In the paper, we investigate the use of reinforcement learning in CBR for estimating and managing a legacy case base for playing the game of Tetris. Each case corresponds to a loc...
In this paper, we present methods to analyze dialog coherence that help us to automatically distinguish between coherent and incoherent conversations. We build a machine learning ...
This paper analyzes the impact of several lexical and grammatical features in automated assessment of students' finegrained understanding of tutored concepts. Truly effective...
In this paper, we model large support vector machines (SVMs) by smaller networks in order to decrease the computational cost. The key idea is to generate additional training patte...
Pramod Lakshmi Narasimha, Sanjeev S. Malalur, Mich...
The problem of recognizing textual entailment (RTE) has been recently addressed using syntactic and lexical models with some success. Here, we further explore this problem, this t...