Automatic multilingual text classification according to pre-established categories defined in a model. The algorithm used combines statistic classification with rule-based filtering, which allows to obtain a high degree of precision for very different environments. Three models available: IPTC (International Press Telecommunications Council standard), EuroVocs and Corporate Reputation model. Languages covered are Spanish, English, French, Italian, Portuguese and Catalan.
Text Clustering is MeaningCloud's solution for automatic document clustering, i.e., the task of grouping a set of texts in such a way that texts in the same group (called a cluster) are more similar to each other than to those in other clusters.
Summarization is MeaningCloud's solution to extract a summary for a given document, selecting the most relevant sentences in it to try to sum up what it is about. This process does not take into account the language when it evaluates the importance of a sentence, which means that it's language independent and can be applied to documents in any language.
The Document Structure Analysis extracts different sections of a given document with markup content (which includes formatted documents such as PDF or Microsoft Word files), including the title, headings, abstract and parts of an email. This process, even though it takes into account some language markers, is based mainly in the markup of the document, so it can be applied to documents in any language.
Deep Categorization is MeaningCloud's solution for in-depth rule-based categorization. It assigns one or more categories to a text, using a very detailed rule-based language that allows you to identify very specific scenarios and patterns using a combination of morphological, semantic and text rules.
Topics Extraction tags locations, people, companies, dates and many other elements appearing in a text written in Spanish, English, French, Italian, Portuguese or Catalan. This detection process is carried out by combining a number of complex natural language processing techniques that allow to obtain morphological, syntactic and semantic analyses of a text and use them to identify different types of significant elements.
This service provides detailed linguistic information for a given text in English, Spanish, French, Italian, Portuguese and Catalan. There are three operating modes that cover different aspects of the morphosyntactic and semantic analysis: Lemmatization, which provides the lemmas of the different words in a text; PoS tagging: which provides not only the grammatical category of a word, including semantic information about that word; Syntactic analysis: that provides a thorough syntactic analysis, giving a complete syntactic tree where the leaves represent the most basic elements and their morphological and semantic analyses.
