In this paper, we focus on lexical semantics, a key issue in Natural Language Processing (NLP) that tends to converge with conceptual Knowledge Representation (KR) and ontologies....
Establishing a clean relationship between a robot’s spatial model and natural language components is a non-trivial task, but is key to designing verbally controlled, navigating s...
Robert J. Ross, Hui Shi, Tillman Vierhuff, Bernd K...
Most natural language database interfaces suffer from the translation knowledge portability problem, and are vulnerable to ill-formed questions because of their deep analysis. To a...
This paper reports on refinements and extensions to the MathLang framework that add substantial support for natural language text. We show how the extended framework supports mult...
ConceptNet is a very large semantic network of commonsense knowledge suitable for making various kinds of practical inferences over text. ConceptNet captures a wide range of common...
When implementing a tutoring system that attempts a deep understanding of students’ natural language explanations, there are three basic approaches to choose between; symbolic, i...
A number of content management tasks, including term categorization, term clustering, and automated thesaurus generation, view natural language terms (e.g. words, noun phrases) as...
Alberto Lavelli, Fabrizio Sebastiani, Roberto Zano...
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
A key to improving at any task is frequent feedback from people whose opinions we care about: our family, friends, mentors, and the experts. However, such input is not usually ava...
We present a generic natural language processing (NLP) architecture, acronym QTIL, based on a system of cooperating multiple agents (Q/A, T, I, and L agents) which can be used in ...