In the digital world, semantic technologies and procedures automate the classification of digital content and enable the assignment of content to specific topic areas. Semantic methods find a practical application where the optimal management of a constantly growing amount of online content contributes to the strategic goals of an organisation. Publishers, archives and service departments are potential beneficiaries of semantic solutions.
The origin of content does not play a decisive role in the analysis of meaning. Semantic analysis algorithms process content from any available internal and external source. These include content management systems (CMSs), customer relationship management solutions (CRMs), and also files from the company’s own intranet and openly accessible sources on the internet.
Text, audio, video or office formats – basically any digital file format is suitable for semantic enrichment. Even though images and phonetic phenomena can be analysed in principle, the semantic enrichment of texts is the most mature.
Semantic enrichment of texts analyses headings, teasers, texts and metadata for all content. An algorithm searches the content for specific keywords and identifies so-called entities, i.e. relevant persons, places, organisations, products, events and general terms.
The algorithm then calculates relevant information to determine how important an entity is for the meaning of a text. In a third step, semantic enrichment identifies recognized entities in a text. Structured, machine-readable data is thus created from unstructured texts and content is generated that can be used digitally by any company.
In terms of concrete solutions, semantic enrichment supports, for example, the editors of news portals with the automatic indexing of articles. Semantic enrichment also provides tools for creating topic pages that aggregate all contributions to a news website in a user-friendly way.
The automation of content creation enables a high degree of efficiency in the editorial process. The effects of this have results for the visibility of the information provided in search engines, for user-friendliness and the economic utilisation of digital contents.
Not to be confused with semantic enrichment is semantic tagging. Semantic tagging is the process of mapping an item from an ontology to a document, usually a computer file or website. The goal of semantic tagging is to describe a document in order to provide better access later. Semantic tagging also helps to integrate the tagged document with other resources that are also related to the same ontology.