Cooperative answering through controlled query relaxation

IEEE Expert ◽  
1997 ◽  
Vol 12 (5) ◽  
pp. 48-59 ◽  
Author(s):  
T. Gaasterland
Keyword(s):  
Query Relaxation ◽  
Cooperative Answering

Approximate Query Answering with Knowledge Hierarchy

2010 ◽  
pp. 189-203
Author(s):  
Wookey Lee ◽  
Myung-Keun Shin ◽  
Soon Young Huh ◽  
Donghyun Park ◽  
Jumi Kim
Keyword(s):  
Cost Model ◽  
Numerical Data ◽  
Query Answering ◽  
Query Relaxation ◽  
Approximate Query Answering ◽  
Novel Method ◽  
Approximate Query ◽  
Semantic Distances ◽  
Ranking Measures ◽  
Knowledge Hierarchy

Approximate Query Answering is important for incorporating knowledge abstraction and query relaxation in terms of the categorical and the numerical data. By exploiting the knowledge hierarchy, a novel method is addressed to quantify the semantic distances between the categorical information as well as the numerical data. Regarding that, an efficient query relaxation algorithm is devised to modify the approximate queries to ordinary queries based on the knowledge hierarchy. Then the ranking measures work very efficiently to cope with various combinations of complex queries with respect to the number of nodes in the hierarchy as well as the corresponding cost model.

When the answer comes into question in question-answering: survey and open issues

2012 ◽  
Vol 19 (1) ◽  
pp. 1-32 ◽  
Author(s):  
ANA CRISTINA MENDES ◽  
LUÍSA COHEUR
Keyword(s):  
Question Answering ◽  
Information Sources ◽  
State Of The Art ◽  
Research Community ◽  
The State ◽  
Present Survey ◽  
Cooperative Answering ◽  
Open Issues

AbstractThe answer determines the success of a Question-Answering (QA) system. In redundancy-based QA systems, a common approach is to extract the candidate answers from the information sources and select the most frequent answers as the final answers. However, this strategy has some pitfalls. For instance, if a system is not able to detect equivalences between the candidate answers, their frequencies might be erroneously calculated. Moreover, the user who posed the question should also be taken into account when answering: different persons require different (correct) answers. This can involve the use of suitable vocabulary and/or information details. In these situations, the generation of a response can be a more suitable strategy, instead of the extraction and direct retrieval of the answer from the information sources. The present survey targets the state of the art in the answering task in QA under three different lines of research. First, we present several works that focus on relating candidate answers. Then, we recover the concept of cooperative answer – a correct, useful, and non-misleading answer – and we bring up attempts to address cooperative answering. Finally, we investigate the research community endeavors on response generation. We will also present our perspective on each of these three topics throughout this paper.

QoS-aware query relaxation for service discovery with business rules

2016 ◽  
Vol 60 ◽  
pp. 1-12 ◽  
Author(s):  
Shang-Pin Ma ◽  
Kuan Y. Chang ◽  
Jing-Hong Lin ◽  
Chih-Chun Ma ◽  
Jui-Hsaing Lin
Keyword(s):  
Service Discovery ◽  
Business Rules ◽  
Query Relaxation

Query relaxation by structure and semantics for retrieval of logical Web documents

2002 ◽  
Vol 14 (4) ◽  
pp. 768-791 ◽  
Author(s):  
Wen-Syan Li ◽  
K.S. Candan ◽  
Quoc Vu ◽  
D. Agrawal
Keyword(s):  
Query Relaxation ◽  
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