Knowledge querying in the conceptual graph model: The RAP module

Author(s):  
Olivier Guinaldo ◽  
Ollivier Haemmerlé
Keyword(s):  
Author(s):  
Rallou Thomopoulos

This chapter deals with the problem of the cooperation of heterogeneous knowledge for the construction of a domain expertise, and more specifically for the discovery of new unexpected knowledge. Two kinds of knowledge are taken into account: • Expert statements. They constitute generic knowledge which rises from the experience of domain experts and describes commonly admitted mechanisms that govern the domain. This knowledge is represented as conceptual graph rules, which has the advantage to combine a logic-based formalism and an equivalent graphical representation, essential for non-specialist users (Bos, 1997). • Experimental data, given by international literature of the domain. They are represented in the relational model. These numerous data describe in detail, in a quantitative way, experiments that were carried out to deepen the knowledge of the domain, and the obtained results. These results may confirm the knowledge provided by the expert statements – or not. The cooperation of both kinds of knowledge aims, firstly, at testing the validity of the expert statements within the experimental data, secondly, at discovering refinements of the expert statements to consolidate the domain expertise. Two major differences between the two formalisms are the following. Firstly, the conceptual graphs represent knowledge at a more generic level than the relational data. Secondly, the conceptual graph model includes an ontological part (hierarchized vocabulary that constitutes the support of the model), contrary to the relational model. We introduce a process that allows one to test the validity of expert statements within the experimental data, that is, to achieve the querying of a relational database by a system expressed in the conceptual graph formalism. This process is based on the use of annotated conceptual graph patterns. When an expert statement appears not to be valid, a second-step objective is to refine it. This refinement consists of an automatic exception rule learning which provides unexpected knowledge in regard of previously established knowledge. The examples given in this chapter have been designed using the CoGui tool (http://www.lirmm. fr/cogui/) and concern a concrete application in the domain of food quality.


1995 ◽  
Vol 34 (04) ◽  
pp. 345-351 ◽  
Author(s):  
A. Burgun ◽  
L. P. Seka ◽  
D. Delamarre ◽  
P. Le Beux

Abstract:In medicine, as in other domains, indexing and classification is a natural human task which is used for information retrieval and representation. In the medical field, encoding of patient discharge summaries is still a manual time-consuming task. This paper describes an automated coding system of patient discharge summaries from the field of coronary diseases into the ICD-9-CM classification. The system is developed in the context of the European AIM MENELAS project, a natural-language understanding system which uses the conceptual-graph formalism. Indexing is performed by using a two-step processing scheme; a first recognition stage is implemented by a matching procedure and a secondary selection stage is made according to the coding priorities. We show the general features of the necessary translation of the classification terms in the conceptual-graph model, and for the coding rules compliance. An advantage of the system is to provide an objective evaluation and assessment procedure for natural-language understanding.


2008 ◽  
Vol 1 (06) ◽  
pp. 329-334
Author(s):  
S. Rabih ◽  
C. Turpin ◽  
S. Astier

Author(s):  
A. N. Bozhko

Computer-aided design of assembly processes (Computer aided assembly planning, CAAP) of complex products is an important and urgent problem of state-of-the-art information technologies. Intensive research on CAAP has been underway since the 1980s. Meanwhile, specialized design systems were created to provide synthesis of assembly plans and product decompositions into assembly units. Such systems as ASPE, RAPID, XAP / 1, FLAPS, Archimedes, PRELEIDES, HAP, etc. can be given, as an example. These experimental developments did not get widespread use in industry, since they are based on the models of products with limited adequacy and require an expert’s active involvement in preparing initial information. The design tools for the state-of-the-art full-featured CAD/CAM systems (Siemens NX, Dassault CATIA and PTC Creo Elements / Pro), which are designed to provide CAAP, mainly take into account the geometric constraints that the design imposes on design solutions. These systems often synthesize technologically incorrect assembly sequences in which known technological heuristics are violated, for example orderliness in accuracy, consistency with the system of dimension chains, etc.An AssemBL software application package has been developed for a structured analysis of products and a synthesis of assembly plans and decompositions. The AssemBL uses a hyper-graph model of a product that correctly describes coherent and sequential assembly operations and processes. In terms of the hyper-graph model, an assembly operation is described as shrinkage of edge, an assembly plan is a sequence of shrinkages that converts a hyper-graph into the point, and a decomposition of product into assembly units is a hyper-graph partition into sub-graphs.The AssemBL solves the problem of minimizing the number of direct checks for geometric solvability when assembling complex products. This task is posed as a plus-sum two-person game of bicoloured brushing of an ordered set. In the paradigm of this model, the brushing operation is to check a certain structured fragment for solvability by collision detection methods. A rational brushing strategy minimizes the number of such checks.The package is integrated into the Siemens NX 10.0 computer-aided design system. This solution allowed us to combine specialized AssemBL tools with a developed toolkit of one of the most powerful and popular integrated CAD/CAM /CAE systems.


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