Semantic Engine for Text Management using Ontology and Knowledge Engineering (SETMOKE)
The amount of textual information available is increasing continuously however, the human capacity to understand and process information is limited. The phenomena of information overload When a lot of redundant information is available and it is difficult or impossible for humans to understand and handle it. Tackling the problem of information overload is necessary for utilizing the information in an effective manner. Thus, in the current era, automatic processing of available unstructured textual information is a big challenge. Therefore, the need of set of generic tools for automated extraction of useful knowledge and its presentation to the user in flexible ways is evident. We propose an open interface Semantic Engine for Text Management using Ontology and Knowledge Engineering (SETMOKE), to deal with this information overload semantically.
The initial objectives of SETMOKE are as follows:
- Understand the provided textual data semantically
- Transform the given unstructured textual data into structured data (ontological database)
- Provide a query and inference mechanism to extract knowledge from the stored Ontological Database (ODB)
- Open interface availability as plug-in for other applications