The application of Case Based Reasoning on Q&A system

Peng Han; Rui Min Shen; Fan Yang; Qiang Yang

doi:10.1007/3-540-36187-1_62

The application of Case Based Reasoning on Q&A system

Peng Han, Rui Min Shen, Fan Yang, Qiang Yang

Research output: Chapter in Book/Conference Proceeding/Report › Book Chapter › peer-review

5 Citations (Scopus)

Abstract

Q&A (Question and Answer) system is an important aiding tool for people to obtain knowledge and information from the Internet. In this paper, we introduce CBR (Case Based Reasoning) into traditional Q&A system to increase the efficiency and accuracy of retrieving the solution. We put forward an interactive and introspective Q&A engine which uses keywords of the question to trigger the case and sorts the results by the relationship. The engine can also modify the weights of the keywords dynamically based on the feedbacks of the user. Inside the engine, we use a feature-weight maintenance algorithm to increase the accuracy. We also extend the 2-layer architecture of CBR to a 3-layer structure to make the system more scalable and maintainable.

Original language	English
Title of host publication	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Pages	704-713
Number of pages	10
Volume	2557
DOIs	https://doi.org/10.1007/3-540-36187-1_62
Publication status	Published - 2002
Externally published	Yes

Access to Document

10.1007/3-540-36187-1_62

Cite this

@inbook{544575efc49041009d6da110d28e0e2a,

title = "The application of Case Based Reasoning on Q\&A system",

abstract = "Q\&A (Question and Answer) system is an important aiding tool for people to obtain knowledge and information from the Internet. In this paper, we introduce CBR (Case Based Reasoning) into traditional Q\&A system to increase the efficiency and accuracy of retrieving the solution. We put forward an interactive and introspective Q\&A engine which uses keywords of the question to trigger the case and sorts the results by the relationship. The engine can also modify the weights of the keywords dynamically based on the feedbacks of the user. Inside the engine, we use a feature-weight maintenance algorithm to increase the accuracy. We also extend the 2-layer architecture of CBR to a 3-layer structure to make the system more scalable and maintainable.",

author = "Peng Han and Shen, \{Rui Min\} and Fan Yang and Qiang Yang",

year = "2002",

doi = "10.1007/3-540-36187-1\_62",

language = "English",

isbn = "3540001972",

volume = "2557",

pages = "704--713",

booktitle = "Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)",

}

TY - CHAP

T1 - The application of Case Based Reasoning on Q&A system

AU - Han, Peng

AU - Shen, Rui Min

AU - Yang, Fan

AU - Yang, Qiang

PY - 2002

Y1 - 2002

N2 - Q&A (Question and Answer) system is an important aiding tool for people to obtain knowledge and information from the Internet. In this paper, we introduce CBR (Case Based Reasoning) into traditional Q&A system to increase the efficiency and accuracy of retrieving the solution. We put forward an interactive and introspective Q&A engine which uses keywords of the question to trigger the case and sorts the results by the relationship. The engine can also modify the weights of the keywords dynamically based on the feedbacks of the user. Inside the engine, we use a feature-weight maintenance algorithm to increase the accuracy. We also extend the 2-layer architecture of CBR to a 3-layer structure to make the system more scalable and maintainable.

AB - Q&A (Question and Answer) system is an important aiding tool for people to obtain knowledge and information from the Internet. In this paper, we introduce CBR (Case Based Reasoning) into traditional Q&A system to increase the efficiency and accuracy of retrieving the solution. We put forward an interactive and introspective Q&A engine which uses keywords of the question to trigger the case and sorts the results by the relationship. The engine can also modify the weights of the keywords dynamically based on the feedbacks of the user. Inside the engine, we use a feature-weight maintenance algorithm to increase the accuracy. We also extend the 2-layer architecture of CBR to a 3-layer structure to make the system more scalable and maintainable.

UR - https://www.scopus.com/pages/publications/84857742458

U2 - 10.1007/3-540-36187-1_62

DO - 10.1007/3-540-36187-1_62

M3 - Book Chapter

AN - SCOPUS:84857742458

SN - 3540001972

SN - 9783540001973

VL - 2557

SP - 704

EP - 713

BT - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

ER -

The application of Case Based Reasoning on Q&A system

Abstract

Access to Document

Other files and links

Fingerprint

Cite this