What is the difference between taxonomy and thesaurus

Thesauri and taxonomies are specific kinds of controlled vocabularies, but not all controlled vocabularies are thesauri or taxonomies. A taxonomy is typically a controlled vocabulary with a hierarchical structure, with the understanding that there are different definitions of a hierarchy. Terms within a taxonomy have relations to other terms within the taxonomy. Taxonomies are often displayed as a tree structure.

Terms within a taxonomy are often called "nodes. This is referred to as a polyhierarchy. Another type of taxonomy, with a more limited hierarchy, comprises multiple sub-taxonomies or "facets", whereby the top-level node of each represents a different type of taxonomy, attribute, or context.

This is used on post-coordinated searching, whereby the user chooses a combination of nodes, one from each facet. The use of equivalent synonyms or see references may or many not exist in a taxonomy. If a hierarchy is not too large and can be browsed, and especially if there are polyhierarchies, then there is less of a need for nonpreferred variants.

A thesaurus , as used in information science and literature retrieval, is essentially a controlled vocabulary following a standard structure, where all terms in the thesaurus have relationships to each other. This does not need to be done enterprise-wide all at once; it can be done in stages, starting with one function such as marketing or customer support.

However, the initiative should be carried out with a long-term roadmap in mind that sets up a framework for future steps. To get the full benefits of ontology, it should be implemented enterprise-wide.

A few years back, I was attending an executive presentation of project findings and recommendations for an outdoor products manufacturing company. When you consider how customers interact with organizations these days, it quickly becomes apparent that much of that interaction is through digital channels.

The question is, how do we make it the most relevant and seamless experience possible, given the needs and objectives of the user, and what data can we leverage to do so? In addition to voice of the customer feedback through surveys and social media monitoring which provide high-level themes , three principal ways of leveraging data can be used in order to create an excellent customer experience:.

Personalization comes in multiple shapes and forms, many of which businesses can put to effective use. But they shouldn't make the mistake of launching all of them at once. An incremental approach works well here. And a good place to start is product hierarchies. Privacy Policy Terms of Service. All Posts. What is the Difference between Taxonomy and Ontology? It is a Matter of Complexity. What is taxonomy? Tools are classified into power tools and hand tools, and hand tools classified into products like hammers and wrenches , and then further broken down into different brands and sizes of wrenches.

How are ontologies different? This could include customers who are consumers and contractors, and sub-categories within those, such as contractors who are roofers and electricians. By relating categories of users with products sold in stores, an ontology would present a list of products relevant to those users. Underlying characteristics of ontologies Ontologies are a key ingredient for personalization and proactive marketing, as well as for customer support.

Benefits of ontologies for intelligent virtual assistants and bots Another motivation for the use is that ontologies can also support advanced capabilities to drive intelligent virtual assistants and bots. Detecting intent An important characteristic of successful bots is their ability to detect intent , an ability that is fostered by being ontology-based. Why information architecture is important to ontology success In order to function at an optimal level, taxonomies and ontologies both require a solid information architecture IA , which addresses how to organize and structure enterprise content.

Chantal Schweizer Chantal Schweizer is a taxonomy professional with over 10 years of experience in Product Information and Taxonomy. Recent Popular Related Posts. Subscribe to the Insights feed. Recent Posts. Seth Earley. How Personalized Customer Experience Leads to Competitive Advantage When you consider how customers interact with organizations these days, it quickly becomes apparent that much of that interaction is through digital channels.

Personalization - 3 Ways to Use Data to Guide Decisions Personalization comes in multiple shapes and forms, many of which businesses can put to effective use. They sufficiently equivalent, though, for most taxonomies. This brings us to another important point. Variants should be roughly equivalent within the context of the taxonomy and the body of content it is used to index. What serves well as a variant in one taxonomy might not be suitable for the same term in another taxonomy.

While a taxonomy could be browsed, it is more common for a taxonomy to be searched. The user searches for terms within the taxonomy, matching search strings against any variant of a term, if not the preferred term itself. The search does not have to be an exact match and may match to taxonomy terms that have at least the same words in any order and grammatically stemmed versions of the words such as education and educational. With this in mind, taxonomists do not need to create variants for every possible variation of a term, as the search technology will be able to take care of some of that.

As for sources for variants, other than the taxonomist's own knowledge of language, any term variations in sample source documents to be indexed should be considered.