GDL

Journal from gdlhub / 2021-08-24 11:54:52
Oleh : Marco Antonio Calijorne Soares, Fernando Silva Parreiras, King Saud University
Dibuat : 2021-08-04, dengan 0 file

Keyword : Question answering systems, Natural language processing, Information retrieval
Url : http://www.sciencedirect.com/science/article/pii/S131915781830082X
Sumber pengambilan dokumen : Web

Background

Question Answering (QA) systems enable users to retrieve exact answers for questions posed in natural language.


Objective

This study aims at identifying QA techniques, tools and systems, as well as the metrics and indicators used to measure these approaches for QA systems and also to determine how the relationship between Question Answering and natural language processing is built.


Method

The method adopted was a Systematic Literature Review of studies published from 2000 to 2017.


Results

130 out of 1842 papers have been identified as describing a QA approach developed and evaluated with different techniques.


Conclusion

Question Answering researchers have concentrated their efforts in natural language processing, knowledge base and information retrieval paradigms. Most of the researches focused on open domain. Regarding the metrics used to evaluate the approaches, Precision and Recall are the most addressed.

Deskripsi Alternatif :

Background

Question Answering (QA) systems enable users to retrieve exact answers for questions posed in natural language.


Objective

This study aims at identifying QA techniques, tools and systems, as well as the metrics and indicators used to measure these approaches for QA systems and also to determine how the relationship between Question Answering and natural language processing is built.


Method

The method adopted was a Systematic Literature Review of studies published from 2000 to 2017.


Results

130 out of 1842 papers have been identified as describing a QA approach developed and evaluated with different techniques.


Conclusion

Question Answering researchers have concentrated their efforts in natural language processing, knowledge base and information retrieval paradigms. Most of the researches focused on open domain. Regarding the metrics used to evaluate the approaches, Precision and Recall are the most addressed.

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