China
Africa
Explore chapters and articles related to this topic
Metadata Schemes, Structures, and Encoding
Published in Mike Cox, Linda Tadic, Ellen Mulder, Descriptive Metadata for Television An End-to-End Introduction, 2006
Mike Cox, Linda Tadic, Ellen Mulder
Metadata values are the actual words and numbers contained in the fields (structure) according to proscribed rules. Controlled vocabularies should be used as values wherever possible to maintain consistency in inputting and retrieval. A controlled vocabulary is a list of terms or names that cluster variants of a term or name around a preferred heading. In broadcasting, controlled vocabularies can most often be found supplying authorized terms for names, genres, subjects, and media formats.
An European network of decentralized portals enabling e-business with building regulations – The CONNIE project
Published in Manuel Martínez, Raimar Scherer, eWork and eBusiness in Architecture, Engineering and Construction, 2020
T. Cerovsek, G. Gudnason, C. Lima
There are many different kinds of controlled vocabularies. The common ones are (Figure 5): – Preferred terms (“pick lists”): frequently used to display small sets of terms that are to be used for quite narrowly defined purposes such as a web pulldown list or list of menu choices.– Synonym rings: used behind-the-scenes to enhance retrieval, especially in an environment in which the indexing uses an uncontrolled vocabulary and/or there is no indexing as when searching full text.– Taxonomies: often created and used in indexing applications and for web navigation. Because of their (usually simple) hierarchical structure, they are effective at leading users to the most specific terms available in a particular domain.– Thesauri: these are the most typical form of controlled vocabulary developed for use in indexing and searching applications because they provide the richest structure and cross-reference environment. Controlled vocabularies are essentially used for: – Translation: provide a means for converting the natural language of authors, indexers, and users into a vocabulary that can be used for indexing and IR.– Consistency: promote uniformity in term format and in the assignment of terms.– Indication of relationships: indicate semantic relationships among terms.– Label and browse: provide consistent and clear hierarchies in a navigation system to help users locate desired content objects.– Retrieval: serve as a searching aid in locating content objects.
A non-conformance rate prediction method supported by machine learning and ontology in reducing underproduction cost and overproduction cost
Published in International Journal of Production Research, 2021
Bongjun Ji, Farhad Ameri, Hyunbo Cho
In this particular manufacturer, employees generally use unstructured natural in various documents to communicate information about work orders, product features, and quality issues. The inherent ambiguity of natural language often results in miscommunication or information loss. Utilising ontology-driven controlled vocabulary will promote interoperability and semantic information exchange across various organisational units. Also, ontology can be used to integrate information related to the non-conformance rate across multiple databases. Additionally, through using a formal ontology, it is possible to express work orders in a structured way and therefore, calculate semantic similarity between them. In this way, one can retrieve similar past work orders with a high level of precision.
Nomenclature for offsite construction
Published in Building Research & Information, 2022
Jinfeng Lou, Weisheng Lu, Jinying Xu, Xiao Li, Jing Wang
While naming rules stipulate the syntax of naming, a controlled vocabulary is still needed to ensure common understanding of names. A controlled vocabulary is limited, with one and only one term for one concept (Olson, 2002). Benefits are: (1) recognizable abbreviations are likely to be developed to ensure names are concise; (2) enhanced common understanding of stakeholders, alleviating confusion in project collaboration from unclear references; (3) avoiding disorder in naming from simultaneously following different taxonomy systems; and (4) no duplicate terms express the same concept so that the recall and accuracy of searching are improved. The suggested vocabularies are also presented in Table 6.