Technology & Impact
Semantically Enabled Systems aim to understand the text being reviewed, in order to decide whether the text is relevant or not. It does this by analyzing the words and sentence construction. These techniques allow us to find the information we are looking for, even though it may be in a different form than we were expecting.
However, it is not as straight forward as it sounds.
- Morphology - Words are written differently depending on their tense (eg tells, telling, tell);
- Sentence structure – sentences appearing to be similar in structure often differ in analysis:
- John pulled the door with a bang (i.e. bang refers to the door)
- John pulled the door with a grin (i.e. grin refers to John)
- Word meaning – Words can have multiple meanings:
- bank (i.e. Noun a repository for money)
- bank (i.e. Noun meaning the edge of a river)
- bank (i.e. Verb meaning to place in a repository)
The context is necessary to determine which meaning is correct.
Semantically Enabled Systems use a variety to tools to deconstruct the text, identify named entities (eg people) and disambiguate the meaning of words given their context. They also have other key components:
- Ontologies – data structures that define entities/classes and their relationships to other entities. For instance, Teacher might be a type of a more general class of Worker.
- Dictionaries – to provide real world context
- Synsets - to provide other words with similar meanings
- Gazetteers - to provide context/domain specific vocabulary
- Rules Engines – artificial intelligence based programming environments to enable the development of code to differentiate or infer meaning.
