Automated content tagging is an approach to solving the challenge of finding the right content
Organizations create large volumes of content. They need to easily search and access this content later. Such content is usually in an unstructured form, such as documents, images, and videos. We make it easy and quick to search your content with 2 specific steps. The first step is to identify the keywords from within the content or its description, and then attach the keywords as tags or labels to the content.
- • The process is difficult, cumbersome, time taking, and error-prone.
- • Typing errors or reading a keyword might hide a document from the search applications.
- • Identifying keywords in a document is a subjective activity driven by the experience and knowledge of the person performing it.
- • The size of the content can make it difficult to correctly identify all keywords.
- • Important keywords can get missed and useless or extra keywords might get added causing too few or too many results during the search.
- • Understanding the correct context while tagging and classifying is also important.
While it sounds simple, the process of identifying the correct keywords and tagging them to the content has several challenges:
- • It performs smart auto-tagging of content using advanced text-search techniques.
- • It uses self-learning algorithms that continue to improve their efficiency with each execution.
- • It uses an ever-growing set of business vocabulary to recognize context and keywords uniformly.
- • It can handle large sizes and volumes of content with ease and quickly produce a tag cloud for the content.
- • The application is highly context-sensitive and provides simple mechanisms to configure the workflows and rules.
The tags generated by the application make it easy to locate specific contents during a search. Employees, who used to perform such activities manually, now get more time to focus on the core business activities thereby driving better business results.