An approach to characterize graded entailment of arguments through a label-based framework

نویسندگان

Maximiliano Celmo Budán

Gerardo I. Simari

Ignacio Darío Viglizzo

Guillermo Ricardo Simari

چکیده

a Departamento de Ciencias e Ing. de la Computación, Universidad Nacional del Sur (UNS), Instituto de Ciencias e Ing. de la Computación (ICIC UNS–CONICET), San Andres 800, (8000) Bahía Blanca, Argentina b Departamento de Matemática, Universidad Nacional del Sur (UNS), Av. Alem 1253, (8000) Bahía Blanca, Argentina c Departamento de Matemática, Universidad Nacional de Santiago del Estero, Belgrano(s) 1912, (4200) Capital, Sgo. del Estero, Argentina

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A New Framework for Distributed Multivariate Feature Selection

Feature selection is considered as an important issue in classification domain. Selecting a good feature through maximum relevance criterion to class label and minimum redundancy among features affect improving the classification accuracy. However, most current feature selection algorithms just work with the centralized methods. In this paper, we suggest a distributed version of the mRMR featu...

متن کامل

Graded Entailment for Compositional Distributional Semantics

The categorical compositional distributional model of natural language provides a conceptually motivated procedure to compute the meaning of sentences, given grammatical structure and the meanings of its words. This approach has outperformed other models in mainstream empirical language processing tasks. However, until now it has lacked the crucial feature of lexical entailment – as do other di...

متن کامل

Towards a Benchmark of Natural Language Arguments

The connections among natural language processing and argumentation theory are becoming stronger in the latest years, with a growing amount of works going in this direction, in different scenarios and applying heterogeneous techniques. In this paper, we present two datasets we built to cope with the combination of the Textual Entailment framework and bipolar abstract argumentation. In our appro...

متن کامل

Representing Meaning with a Combination of Logical and Distributional Models

NLP tasks differ in the semantic information they require, and at this time no single semantic representation fulfills all requirements. Logic-based representations characterize sentence structure, but do not capture the graded aspect of meaning. Distributional models give graded similarity ratings for words and phrases, but do not capture sentence structure in the same detail as logic-based ap...

متن کامل