Increasing interest is being paid to multilingual data mining: the ability to gain information across languages and cluster similar items from different linguistic sources according to their meaning.The challenge of exploiting the large proportion of enterprise information that originates in "unstructured" form has been recognized for decades.In this paper, I have attempted to suggest a new emphasis: the use of large online text collections to discover new facts and trends about the world itself.

The automation of content analysis has allowed a "big data" revolution to take place in that field, with studies in social media and newspaper content that include millions of news items.Using this approach to classifying solutions, application categories include: Many text mining software packages are marketed for security applications, especially monitoring and analysis of online plain text sources such as Internet news, blogs, etc. Go Pub Med is a knowledge-based search engine for biomedical texts.Text mining methods and software is also being researched and developed by major firms, including IBM and Microsoft, to further automate the mining and analysis processes, and by different firms working in the area of search and indexing in general as a way to improve their results."...utilize data-processing machines for auto-abstracting and auto-encoding of documents and for creating interest profiles for each of the 'action points' in an organization.Both incoming and internally generated documents are automatically abstracted, characterized by a word pattern, and sent automatically to appropriate action points." Yet as management information systems developed starting in the 1960s, and as BI emerged in the '80s and '90s as a software category and field of practice, the emphasis was on numerical data stored in relational databases.