Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Over the last decade, support vector machine classifiers (SVMs) have demonstrated
superior generalization performance to many other classification techniques in a variety of …

One of the first steps in building a spoken language understanding (SLU) module for
dialogue systems is the extraction of flat concepts out of a given word sequence, usually …

This work investigates design choices in modeling a discourse scheme for improving
opinion polarity classification. For this, two diverse global inference paradigms are used: a …

Objectives: Detecting hints to public health threats as early as possible is crucial to prevent
harm from the population. However, many disease surveillance strategies rely upon data …

In this paper, we define models for automatically translating a factoid question in natural
language to an SQL query that retrieves the correct answer from a target relational database …

We build an open-source toolkit which implements deterministic learning to support search
and text classification tasks. We extend the mechanism of logical generalization towards …

We extend the mechanism of logical generalization toward syntactic parse trees and attempt
to detect semantic signals unobservable in the level of keywords. Generalization from a …

Support vector machine (SVM) is a state-of-art classification tool with good accuracy due to
its ability to generate nonlinear model. However, the nonlinear models generated are …

Automatically map** natural language semantics into programming languages has
always been a major and interesting challenge in Computer Science. In this paper, we …