<--- Back to Details
First PageDocument Content
Computational linguistics / Natural language processing / Artificial intelligence applications / Artificial intelligence / Question answering / Question / User interface / Yes and no / Information science / Science / Information retrieval
Date: 2004-07-24 18:10:48
Computational linguistics
Natural language processing
Artificial intelligence applications
Artificial intelligence
Question answering
Question
User interface
Yes and no
Information science
Science
Information retrieval

Microsoft Word - QA Short Talk.doc

Add to Reading List

Source URL: people.csail.mit.edu

Download Document from Source Website

File Size: 24,82 KB

Share Document on Facebook

Similar Documents

Information science / Yahoo! Answers / Information retrieval / Question answering / Answer / Internet forum / Questions and answers / Artificial intelligence

Structural Normalisation Methods for Improving Best Answer Identification in Question Answering Communities Grégoire Burel, Paul Mulholland and Harith Alani Knowledge Media Institute, Open University, UK {g.burel, p.mu

DocID: 1xVWO - View Document

Mathematical logic / Logic / Mathematics / Model theory / Automated theorem proving / Predicate logic / Semantics / Logic programming / Resolution / First-order logic / Skolem normal form / Substitution

Theorem-Proving by Resolution as a Basis for Question-Answering Systems Cordell Green Stanford Research Institute Menlo Park, California

DocID: 1xVHV - View Document

Logic / Mathematics / Mathematical logic / Metalogic / Model theory / Syntax / Well-formed formula / First-order logic / Resolution / Logic programming / Tautology

The use of theorem-proving techniques in question-answering systems by C. C O R D E L L G R E E N and BERTRAM RAPHAEL Stanford Research Institute Menlo Park, California

DocID: 1xUl1 - View Document

Mathematical logic / Logic / Model theory / Metalogic / Predicate logic / Formal methods / Resolution / First-order logic / Skolem normal form / Automated theorem proving / Quantifier / Axiom

11 Theorem-Proving by Resolution as a Basis for Question-Answering Systems Cordell Green Stanford Research Institute Menlo Park. California

DocID: 1xUis - View Document

Computing / Computational linguistics / Linguistics / Information science / Artificial neural network / SPARQL / Semantic parsing / Word-sense disambiguation / Semantic Web / Natural language processing / Query language / Question answering

Neural Machine Translation for Query Construction and Composition Tommaso Soru 1 Edgard Marx 1 Andr´e Valdestilhas 1 Diego Esteves 2 Diego Moussallem 1 Gustavo Publio 1 Abstract Research on question answering with know

DocID: 1xU5z - View Document