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Contracts are usually pages long and exist in large quantities, often unstructured in the file system or are stored in systems with poor search options. Enterprise Search applications help to make contracts intelligently searchable, to get a comprehensive overview and not to overlook anything essential.

Contracts or other legal documents are usually available in large quantities and in an unstructured form. Machine learning techniques help classify them, providing a clear ROI for the business.

Even nowadays technical documentation is mostly not valued as good or useful source of information. Too many incomprehensible or unmanageable documents have shaped the past and left behind frustrated or desperate users. Not to mention experts and technicians who prefer to rather trust their experience than long texts and inappropriate illustrations.

In this post I want to go a little deeper into Ludwig Wittgenstein's argument of "meaning is use" (Philosophical Investigations, 1953), and how it can be seen as a philosophical justification for statistical NLP, including machine learning.