IBMM for Inconsistent Data Identification and Adjustment in the AHP/ANP

2012 ◽  
pp. 29-64
Author(s):  
Gang Kou ◽  
Daji Ergu ◽  
Yi Peng ◽  
Yong Shi
Keyword(s):  
Inconsistent Data

scholarly journals Ontology-mediated query answering over temporal and inconsistent data

Semantic Web ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 475-521
Author(s):  
Camille Bourgaux ◽  
Patrick Koopmann ◽  
Anni-Yasmin Turhan
Keyword(s):  
Query Answering ◽  
Inconsistent Data

Spatial Analysis Management Using Inconsistent Data Sources

2020 ◽  
pp. 375-384
Author(s):  
Stanislav Belyakov ◽  
Alexander Bozhenyuk ◽  
Andrey Glushkov ◽  
Igor Rozenberg
Keyword(s):  
Spatial Analysis ◽  
Data Sources ◽  
Inconsistent Data

Accommodating Hierarchies in Relational Databases

2001 ◽  
pp. 194-209
Author(s):  
Ido Millet
Keyword(s):  
Data Structure ◽  
Relational Databases ◽  
Data Retrieval ◽  
Hierarchical Data ◽  
Inconsistent Data ◽  
The Cost

Relational databases and the current SQL standard are poorly suited to retrieval of hierarchical data. After demonstrating the problem, this chapter describes how two approaches to data denormalization can facilitate hierarchical data retrieval. Both approaches solve the problem of data retrieval, but as expected, come at the cost of difficult and potentially inconsistent data updates. This chapter then describes how we can address these update-related shortcomings via back-end (triggers) logic. Using a proper combination of denormalized data structure and back-end logic, we can have the best of both worlds: easy data retrieval and simple, consistent data updates.

scholarly journals A Hybrid SWIM Data Naming Scheme Based on TLC Structure

2020 ◽  
Vol 12 (9) ◽  
pp. 142
Author(s):  
Zhijun Wu ◽  
Bohua Cui
Keyword(s):  
Information Management ◽  
Search Time ◽  
The Other ◽  
Bloom Filters ◽  
Content Structure ◽  
Inconsistent Data ◽  
State Aggregation ◽  
Hybrid Data ◽  
Better Than

Aiming at the problem of low interconnection efficiency caused by the wide variety of data in SWIM (System-Wide Information Management) and the inconsistent data naming methods, this paper proposes a new TLC (Type-Length-Content) structure hybrid data naming scheme combined with Bloom filters. This solution can meet the uniqueness and durability requirements of SWIM data names, solve the “suffix loopholes” encountered in prefix-based route aggregation in hierarchical naming, and realize scalable and effective route state aggregation. Simulation verification results show that the hybrid naming scheme is better than prefix-based aggregation in the probability of route identification errors. In terms of search time, this scheme has increased by 17.8% and 18.2%, respectively, compared with the commonly used hierarchical and flat naming methods. Compared with the other two naming methods, scalability has increased by 19.1% and 18.4%, respectively.

Example of Diagnostic Inference Based on Uncertain and Partly Inconsistent Data with Application of the Approximate Statement Network

2013 ◽  
Vol 588 ◽  
pp. 127-133
Author(s):  
Damian Skupnik
Keyword(s):  
Sufficient Conditions ◽  
Necessary And Sufficient Conditions ◽  
Technical State ◽  
Diagnostic Model ◽  
Advantages And Disadvantages ◽  
Inconsistent Data ◽  
Interesting Approach ◽  
Multimodal Networks ◽  
Mutual Relations ◽  
Necessary And Sufficient

The paper deals with diagnostic inference based on uncertain and simultaneously partly inconsistent data obtained, e.g. from different sensors. Such cases are very common in diagnostic practice and therefore there is a necessity to deal with them. Interesting approach to solving that kind of tasks consists in an application of the approximate statement network which represents the mutual relations between statements treated as necessary and sufficient conditions. The paper shows an example of applying a diagnostic model represented as the approximate statement network, to inference about technical state of a chosen object. The model was constructed in the REx system which also makes possible creating Bayesian and multimodal networks. Advantages and disadvantages concerning both constructing and using approximate statement networks were briefly described on the basis of obtained results. It seems that presented example shows the possibility of improving supervision systems, especially in regard to the complicated technical objects, by giving a mechanism of avoiding a confusion while making of diagnosis.

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