Title
Improving question answering systems by using the explicit semantic analysis method
Abstract
Question answering (QA) is the task of automatically answering a question posed in natural language. Its applied to several domains, and it is a specific type of information retrieval, that has three components such as question processing, information retrieval, and answer extraction. By analysing the user question, we intend to improve the precision of Question answering systems by focusing namely on the representation of the question itself as a bag of concepts, using the Explicit Semantic Analysis (ESA). In particular, it proposes an approach that decides the relevant answers based on a set of features that describe: (i) the classification of the question, (ii) the generation of the bag of concepts, as well as (iii) the extraction of the relevant answer from the candidate sentences. The representation of the user's question as a bag of concepts allows us to have the greatest number of relevant documents to this question.
Year
DOI
Venue
2016
10.1109/SITA.2016.7772300
2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA)
Keywords
Field
DocType
Question answering system (QAS),information retrieval,natural language,explicit semantic analysis (ESA)
Question answering,Information retrieval,Computer science,Explicit semantic analysis,Natural language,Knowledge extraction,Encyclopedia,Semantics,The Internet,Electronic publishing
Conference
ISSN
ISBN
Citations 
2378-2528
978-1-5090-5782-5
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Said Alami Aroussi100.34
El Habib Nfaoui2156.44
Omar El Beqqali3237.59