36,576 research outputs found
Mistakes in medical ontologies: Where do they come from and how can they be detected?
We present the details of a methodology for quality assurance in large medical terminologies and describe three algorithms that can help terminology developers and users to identify potential mistakes. The methodology is based in part on linguistic criteria and in part on logical and ontological principles governing sound classifications. We conclude by outlining the results of applying the methodology in the form of a taxonomy different types of errors and potential errors detected in SNOMED-CT
Method Exploration of Self-adaptive Entity Matching in Map Fusion
AbstractEntity matching is a crucial and hard technology in map fusion. Current methods still exists some deficiencies, such as matching efficiency is not high, low degree of automation and poor universality, these methods can not meet the matching needs of large data integration, therefore, the urgent need to develop more effective and intelligent methods. This paper analyzed present research situation and existing problems of entity matching, illustrated the necessity of developing self-adaptive entity matching, pointed out urgent research contents and key issues that need to be resolved urgently in self-adaptive entity matching, provided preliminary research scheme of implementing self-adaptive entity matching, finally, introduced characteristics and advantages of self-adaptive entity matching method presented in this paper
An MPEG-7 scheme for semantic content modelling and filtering of digital video
Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users
Digital implementation of the cellular sensor-computers
Two different kinds of cellular sensor-processor architectures are used nowadays in various
applications. The first is the traditional sensor-processor architecture, where the sensor and the
processor arrays are mapped into each other. The second is the foveal architecture, in which a
small active fovea is navigating in a large sensor array. This second architecture is introduced
and compared here. Both of these architectures can be implemented with analog and digital
processor arrays. The efficiency of the different implementation types, depending on the used
CMOS technology, is analyzed. It turned out, that the finer the technology is, the better to use
digital implementation rather than analog
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