Annotation, or tagging, is about attaching names, attributes, comments, descriptions, etc. to a document or to a selected part in a text. It provides additional information (metadata) about an existing piece of data.
It is not tagging
Compared to tagging, which speeds up searching and helps you find relevant and precise information, Semantic Annotation goes one level deeper:
- It enriches the unstructured or semi-structured data with a context that is further linked to the structured knowledge of a domain.
- It allows results that are not explicitly related to the original search.
So, if tagging is about promptly finding the most relevant result, semantic annotation adds diversity and richness to the process.
Semantic Annotation helps to bridge the ambiguity of the natural language when expressing notions and their computational representation in a formal language. By telling a computer how data items are related and how these relations can be evaluated automatically, it becomes possible to process complex filter and search operations.
Imagine your search engine understands that “Barcelona” is a city in “Europe”, it can answer a search query on “IT Companies in Europe” with a link to a document about Yahoo Office in Barcelona, although the exact words “Barcelona” or “Yahoo” never occur in your search query.
Semantics Empowered Web 3.0: Managing Enterprise, Social, Sensor, and Cloud-based Data and Services for Advanced Applications (Synthesis Lectures on Data Management)
Book (Morgan & Claypool Publishers)
Provenance and Annotation of Data and Processes: 5th International Provenance and Annotation Workshop, IPAW 2014, Cologne, Germany, June 9-13, 2014. Revised ... Papers (Lecture Notes in Computer Science)