Scenarios of use
Language hub
A language hub, offered as a Web page or similar, allows users to search for words or phrases and, as a result, provides aggregated information from various sources.
- These sources could be:
- crossTerm
- Online dictionaries
- MT systems
- Glossaries of third-party products.
The language hub combines, filters, orders, and presents the results in the way the company or individual users prefer.
- This way, the users don't need to search in each of the resources individually to
- find information in at least one resource when other resources don't provide any;
- see the most relevant information fast;
- compare information.
Provide term information on terms in texts
In this scenario, users enter text into forms of a system, for example, an ERP or PIM system or any HTML form.
Usually, this is done in order to submit the text to the other system as new or modified content, for example, a product description that will be saved in the system's database.
These texts might contain some terms that are available in crossTerm. The form-based system detects the terms in the text, and marks or displays them. What is more, it may display them along with meta information such as definitions and corporate usage standards, provide links to a web page with full information on the crossTerm entry, or activate suggest improvements.
- The system can thus help the user
- verify that the terms used in the text express the intended concepts .
- verify that the terms used in the text are correct with respect to company standards (example: no terms with meta data flagging them as forbidden should be used) .
- find better wording variants.
Enhance other language technology applications
Many applications use language technology in one way or the other. Search engines, help agents/avatars, and machine translation systems are only some examples.
The results of these systems are significantly enhanced by using domain or company terminology. For example, the results of a machine translation system are fine-tuned by using translation equivalents from crossTerm. What is more, the meta data in the terms can be used to optimize the results so they will reflect company wording standards.