Enriching your documents can make search more effective

Authors: J William Murdock and Sudarshan Thitte

Some search systems allow you to perform linguistic analysis on your documents and store the results of that analysis with those documents. The analysis then acts as an enrichment to the text of the document, because the combination of text and structured analysis results is a more powerful representation of content than plain text alone would be.

For example, IBM Watson Discovery provides a set of built-in natural-language enrichment capabilities. It also allows you to add custom enrichments. Enrichments can include many kinds of language analysis. A particularly popular and useful form of enrichment is entities. Other examples of enrichments include relationships between entities, part of speech of words, types of sentences, etc. IBM Watson Discovery’s built-in enrichments can find common kinds of entities like people or places. Users can add also add custom entity detection capabilities. For example, a business that sells cars and trucks may want separate entity types for cars and for trucks.

This article starts by addressing some common misconceptions about how enrichments can be used in search for Watson Discovery. It then elaborates on some things users sometimes mistakenly expect enrichments to do for search. Finally, it describes some of the ways enrichments can be useful for making your search capability more effective.