It categorizes at the snippet level, discovering the thematic structure of a document, for example, to identify the clauses and passages of a contract that have to do with a certain topic.
Based on semantic rules, you can increase accuracy and recall to levels that are unattainable with other technologies, simply by adding focused rules.
Personal dictionaries can be used to define entities and concepts in certain semantic classes (e.g., brands) that are dynamically used in the rules that define the categories.
It justifies the assignment of the categories to the snippets, showing the expressions that have triggered the corresponding rules, and provides confidence metrics.
For short texts and complex documents
The rule-based technology provides good results both in texts with few words and in documents with multiple sections.
Use the API immediately taking advantage of its pre-prepared categorization models, such as those for the analysis of the Voice of the Customer or the Voice of the Employee included in MeaningCloud Vertical Packs.
Customizable (coming soon)
Use our tools for rule creation and validation to easily build models that are fully adapted to your scenario.
Does not require exhaustive training corpus
Unlike other technologies, semantic rules allow the development of models without the need for an extensive training set, with no more than an abstract understanding of the categories.
Currently available in 6 languages and soon in many more.