IntuScan (the IntuView platform) is based on a bespoke semantic ontology and incorporates hierarchal and attribute information from the ontology both in the NLP algorithms and in extracting implicit information from the texts. The ontology integrates cultural and subject-matter knowledge for deep analysis, categorization and summarization of texts.

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   IntuScan supports the following languages: English, French, Spanish, Italian, Portuguese, Romanian, German, Dutch, Arabic, Farsi, Urdu, Hindi, Indonesian, Malay, Russian, Ukrainian, Czech and Hebrew. Chinese (Mandarin) is in the works.

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   IntuView’s “meaning mining” ontologizes raw textual information and converts the unstructured data into structured semantic data. Using ontological features in the NLP allows the platform to achieve higher accuracy (precision and recall) by mapping polysemic (ambiguous) words and phrases in the text to monosemous (unambiguous) concepts and by aggregating words and phrases that “mean” the same thing in different modes of expression.

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   The IntuView technology is unique. Most of the tools in this field are generic Natural Language Processing (NLP) technologies that perform tasks such as morphological analysis, part of speech (POS) analysis at diverse levels, named entity recognition (NER) or “entity extraction”, generic topic classification and document-level or entity-level sentiment identification. However, these tools are generic by nature, hence they suffer from low levels of precision or recall and are incapable of “reading between the lines” of the text and providing comprehension beyond entity extraction. IntuScan, on the other hand, was designed to emulate as closely as possible the intuition and analytical processes of subject matter experts. IntuScan, therefore, is not merely a “platform”, but a comprehensive solution including an expert knowledgebase and culture and domain specific algorithms that enable in-depth understanding of information that is implicit in the document.

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   IntuScan is a totally out of the box system that works on any data in any supported language with almost no customization.

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   IntuScan provides both Document Level View of the information in a single document and Entity Level View based on Batch/Project level aggregation of information on topics, entities, ideas etc. based on the analysis of the individual texts and aggregating information on elements that are identified as the same elements in different texts (e.g. a summary of all the names, titles, relations, movements, communications, participation in events and organizational affiliations of a given person).

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   IntuScan provides Domain/Topic Categorization based on the linguistic and ontological features of the text.