Unstructured Information Management Architecture (UIMA)

The Unstructured Information Management Architecture (UIMA) allows for the analysis of unstructured text - such as email messages and documents - data which is not in a relational database. UIMA was developed by IBM, and the source code is now freely available through the Apache Software Foundation. See: https://uima.apache.org/ . UIMA helps to find terms and topics in documents, and allow search engines to search for concepts rather than just keywords. Word boundaries are assigned to identify the names of organizations, products, places, or the names of persons. UIMA also helps to extract information to create structured data from the unstructured data.

UIMA tokenizes documents with the following methods:

1. Segmenting strings by whitespace.

2. Regular expression searching to find email addresses; phone numbers; and other common entities.

3. Dictionary word lists.

4. A word stemming algorithm named Snowball.

5. The Tika toolkit to annotate text to extract metadata and structured text in documents.

6. The ConceptMapper annotator to map dictionary entries to text, including multi-term entries to non-contiguous text.

7. The AlchemyAPI annotator to assign text to categories, and perform language identification.

Tokenization separates text into words, characters, or n-grams (syllables, or a sequence of N items from text). UIMA provides a way to analyze unstructured text that is multimodal - contains images, video, and other nontextual data.