Providing metrics and automatic enhancement for hierarchical taxonomies
نویسندگان
چکیده
Taxonomies enable organising information in a human-machine understandable form, but constructing them for reuse and maintainability remains difficult. The paper presents a formal underpinning to provide quality metrics for a taxonomy under development. It proposes a methodology for semi-automatic building of maintainable taxonomies and outlines key features of the knowledge engineering context where the metrics and methodology are most suitable. The strength of the approach presented is that it is applied during the actual construction of the taxonomy. Users provide terms to describe different domain elements, as well as their attributes, and methodology uses metrics to assess the quality of this input. Changes according to given quality constraints are then proposed during the actual development of the taxonomy. (C) 2012 Elsevier Ltd. All rights reserved.
منابع مشابه
Inferring Efficient Hierarchical Taxonomies for MIR Tasks: Application to Musical Instruments
A number of approaches for automatic audio classification are based on hierarchical taxonomies since it is acknowledged that improved performance can be thereby obtained. In this paper, we propose a new strategy to automatically acquire hierarchical taxonomies, using machine learning methods, which are expected to maximize the performance of subsequent classification. It is shown that the optim...
متن کاملAutomated Taxonomy Building by Adopting Discriminant and Characteristic Capabilities
Taxonomies are becoming essential in several fields, playing an important role in a large number of applications, particularly for specific domains. Taxonomies provide efficient tools to people by organizing a huge amount of information into a small hierarchical structure. Taxonomies were originally built by hand, but nowadays the technology permits to produce a vast amount of information. Cons...
متن کاملA hierarchical Convolutional Neural Network for Segmentation of Stroke Lesion in 3D Brain MRI
Introduction: Brain tumors such as glioma are among the most aggressive lesions, which result in a very short life expectancy in patients. Image segmentation is highly essential in medical image analysis with applications, particularly in clinical practices to treat brain tumors. Accurate segmentation of magnetic resonance data is crucial for diagnostic purposes, planning surgical treatments, a...
متن کاملAnalysis of Term Roles Along Taxonomy Nodes by Adopting Discriminant and Characteristic Capabilities
Taxonomies are becoming essential to a growing number of application, particularly for specific domains. Taxonomies, originally built by hand, have been recently focused on their automatic generation. In particular, a main issue on automatic taxonomy building regards the choice of the most suitable features. In this paper, we propose an analysis on how each feature changes its role along taxono...
متن کاملA hierarchical Convolutional Neural Network for Segmentation of Stroke Lesion in 3D Brain MRI
Introduction: Brain tumors such as glioma are among the most aggressive lesions, which result in a very short life expectancy in patients. Image segmentation is highly essential in medical image analysis with applications, particularly in clinical practices to treat brain tumors. Accurate segmentation of magnetic resonance data is crucial for diagnostic purposes, planning surgical treatments, a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Inf. Process. Manage.
دوره 49 شماره
صفحات -
تاریخ انتشار 2013