Approximate Reasoning for Efficient Anytime Induction from Relational Knowledge Bases

Author(s):  
Nicola Di Mauro ◽  
Teresa M. A. Basile ◽  
Stefano Ferilli ◽  
Floriana Esposito
Author(s):  
Maria Vanina Martinez ◽  
Francesco Parisi ◽  
Andrea Pugliese ◽  
Gerardo I. Simari ◽  
V. S. Subrahmanian

2013 ◽  
Vol 333-335 ◽  
pp. 1392-1396
Author(s):  
Ya Lin Zheng

Designing the approximate reasoning matching schemes and the corresponding algorithms with similarity relation Q instead of equivalence relation R can reflect the nature of approximate reasoning and meet more application expectations. In this paper, we introduce the type V matching scheme and the corresponding type V Q-algorithm of multiple multidimensional approximate reasoning with given multidimensional input and multidimensional knowledge bases on strong Q-logic CQ.


1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman

Abstract:Clinical narratives in patient records are usually recorded in free text, limiting the use of this information for research, quality assessment, and decision support. This study focuses on the capture of clinical narratives in a structured format by supporting physicians with structured data entry (SDE). We analyzed and made explicit which requirements SDE should meet to be acceptable for the physician on the one hand, and generate unambiguous patient data on the other. Starting from these requirements, we found that in order to support SDE, the knowledge on which it is based needs to be made explicit: we refer to this knowledge as descriptional knowledge. We articulate the nature of this knowledge, and propose a model in which it can be formally represented. The model allows the construction of specific knowledge bases, each representing the knowledge needed to support SDE within a circumscribed domain. Data entry is made possible through a general entry program, of which the behavior is determined by a combination of user input and the content of the applicable domain knowledge base. We clarify how descriptional knowledge is represented, modeled, and used for data entry to achieve SDE, which meets the proposed requirements.


1998 ◽  
Vol 37 (04/05) ◽  
pp. 327-333 ◽  
Author(s):  
F. Buekens ◽  
G. De Moor ◽  
A. Waagmeester ◽  
W. Ceusters

AbstractNatural language understanding systems have to exploit various kinds of knowledge in order to represent the meaning behind texts. Getting this knowledge in place is often such a huge enterprise that it is tempting to look for systems that can discover such knowledge automatically. We describe how the distinction between conceptual and linguistic semantics may assist in reaching this objective, provided that distinguishing between them is not done too rigorously. We present several examples to support this view and argue that in a multilingual environment, linguistic ontologies should be designed as interfaces between domain conceptualizations and linguistic knowledge bases.


2016 ◽  
pp. 141-149
Author(s):  
S.V. Yershov ◽  
◽  
R.М. Ponomarenko ◽  

Parallel tiered and dynamic models of the fuzzy inference in expert-diagnostic software systems are considered, which knowledge bases are based on fuzzy rules. Tiered parallel and dynamic fuzzy inference procedures are developed that allow speed up of computations in the software system for evaluating the quality of scientific papers. Evaluations of the effectiveness of parallel tiered and dynamic schemes of computations are constructed with complex dependency graph between blocks of fuzzy Takagi – Sugeno rules. Comparative characteristic of the efficacy of parallel-stacked and dynamic models is carried out.


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