Vocabulary Control
Overview
Vocabulary Control is a systematic management of terms. It helps to get higher searchability,better recall and precisionand increased interoperability of data.
Vocabulary Control
- What is a vocabulary control?
Vocabulary control is a set of techniques used to manage and standardize the terms and language used within a specific domain, field, or system. Its primary purpose is to ensure consistency, clarity, and accuracy in communication, particularly in areas like information retrieval, data classification, and knowledge organization.
A controlled vocabulary is an ordered listing of words and Phrases that may be used for content indexing or retrieving through browsing or searching. It normally includes preferred and variant terms and is limited to a well-defined scope or covers a well-defined domain.
The controlled vocabulary performs several tasks:
It typically obviously documents the hierarchical and associative relationships of a concept. It also sets the extent or volume of each subject in addition to that, the controlled vocabulary for word-based systems identifies synonyms and chooses among them one preferred term it identifies multiple concepts that could be expressed by a word or phrase. Vocabulary control provides the solution to overcome difficulties which occur due to the use of natural language of document's subject. Hence, if the control on vocabulary is not applied, then different indices or the same index might be applying different terms for the concept on various occasions while indexing a document which deals with the similar subject and might also utilize different sets of terms that would be used for representing that similar subject at the retrieval time. This would, in fact lead to 'mis-match' and affects the information retrieval.
- What is the need of controlling vocabulary in Information Retrieval?
Controlled vocabulary is a synonym, and the other is standardised or structured vocabulary referring to a predefined list of terms that will be applied for indexing and retrieving the information. It makes for more consistent, accurate, and efficient retrieval systems because controlled language is precise.
- This creates a link between human and artificial language. Instead of depending on the variability or ambiguity of natural language, controlled vocabularies would comprise standardized terms, their synonyms, and hierarchical relations. Such an approach assists in classifying and managing information so that users might search for, find, or understand it more easily.
- It reduces barriers for users who may have different linguistic backgrounds or levels of expertise in a particular domain by providing a standardized language.
- Controlled vocabularies improve the precision of search by eliminating noise from the search results. In this case, when users use standardized terms to search for information, the system can accurately match those terms with the indexed content.
- Interoperability is essential. Controlled vocabularies provide a common language to be shared and understood across other platforms. This interoperability is what would ensure that information exchanged between systems is integrated efficiently and with no hitch towards a more connected and efficient information ecosystem.
- Comprehensive, controlled vocabulary or full taxonomy is required to ensure that machine-assisted or fully automated indexing is comprehensive, irrespective of what is to be indexed. One of the very few companies that can assist clients in generating ANSI/ISO/W3C-compliant taxonomies to make information findable is Access Innovations.
- What are the tools for vocabulary control?
Subject Heading List
- A vocabulary control device relies on a master list of terms, which can be assigned to the documents. Such a master list of terms is known as 'List of Subject Headings'. A list of subject headings contains the preferred terms that are to be made use of in the cataloguing or indexing. In this process, the following benefits are involved:
- Specific and Direct Entry - Specific and direct entry principles require that a document be assigned directly under the most specific subject that correctly and accurately represents its subject content.
- Common Usage - According to this principle, words used to express a subject must be of common usage.
- Consistency and Uniformity- There must be one uniform term chosen out of several synonyms and that term must be applied consistently to all the documents on the topic. Only one is used as the heading in case of variant spellings of the same term or different possible forms of the same headings. According to consistency, a term which is chosen on the basis of common usage may go obsolete with the passage of time. A list of subject headings should use current terminology. In such a situation a subject authority file is to be maintained.
- Thesaurus
It is an ordered list of terms structured in a way that aids in the selection of index terms as well as search terms. A thesaurus differs from a traditional authority list such as Sear's List, in that the terms are not necessarily stand-alone but may be related to other terms. The relationships between the terms are well defined by use of the following standard abbreviations:-
SN Scope Note
UF Used For
BT Broader Term
RT Related Term
SA See Also
Classification Scheme
A classification scheme, in particular a faceted and hierarchical one, is able to illustrate hierarchical, faceted, and phase relationships but often fails to bring out other associative and equivalence relationships. Each type of classification scheme has unique advantages and is designed to suit the special organizational and retrieval needs of the libraries.
•Enumerative Classification Schemes: An enumerative Library classification scheme is a scheme where all the possible classes are enumerated according to specific characteristics. There is a top-down approach whereby a series of subordinate classes are produced and where both simple and complex subjects are listed. The advantage of this scheme is that the structure of the scheme is shown by the notation as far as practicable.
•Faceted Classification Scheme: The opposite of this nature is a faceted classification scheme. It lists not the classes and their corresponding numbers but the different facets-or faces-of every subject or main class with a set of rules to construct class numbers by facet analysis. The facet analysis was a concept proposed by Dr. S. R. Ranganathan for use in his Colon Classification.
•Analytico-Synthetic Classification Scheme: Analytico-Synthetic Library classification schemes resolve some of the problems of enumerative classification schemes. The concept behind this scheme is that the subject of a given document will be divided into its constituent elements. Then, the classification scheme will be used to find notations for each element, which will then be combined according to the prescribed rules to prepare the final class number.
Thesaurofacet
This idea was created for the English Electric Company by Jean Aitchison and associates. In essence, it is a thesaurus combined with a faceted classification system. There are two parts to Thesauro-Facet: an alphabetical thesaurus and a faceted categorisation system. Terms are used twice: once in the schedule and once in the alphabetical thesaurus. The notation or class number serves as the connection between the two places.
- What is a Classaurus?
Additionally, it is a vocabulary control tool that was created by Dr. Ganesh Bhattacharya at DRTC and combines elements of a traditional alphabetical thesaurus and a faceted classification scheme. It is a simple category-based (faceted) systematic method of hierarchical categorisation in the verbal plane that includes all the essential and sufficient elements of a traditional thesaurus for information retrieval.
- What is the difference between natural language and artificial language
1. Natural language develops with social interaction over time. Artificial language, on the other hand, is developed with the support of natural language.
2. Natural language is based on human vocabulary and grammar. Artificial language, however, depends on online as well as offline databases along with vocabulary.
3. The natural language is highly flexible. Artificial language, however, is less flexible.
Natural language is human based language. Artificial language is Machine based language.
4. Natural language can be both a primary and secondary source. Artificial language is always a secondary source.
5. Natural language has no limit to its vocabulary and no complete set of rules to describe its syntax and grammar. While in case of artificial language the information to be represented is limited in variability.
6. The natural language is understandable to masses without any special training, while in case of artificial language user training in the usage of the language is needed. This may minimize chances of errors in usage.