Conceptual search is an advanced approach to searching and classifying large document sets on the basis of similar ideas and concepts, rather than keywords. Conceptual search is extremely beneficial in Early Case Assessment.
Think Google™. If you know what you are looking for, entering a keyword or series of keywords can identify all of the documents in a document set that contain these words. Keyword search works well, but has a number of drawbacks in the eDiscovery process, particularly when used with large document collections.
1. Very time consuming to run a series of searches for a large number of keywords.
2. Keywords can have several meanings - documents with alternative or 'wrong' meanings must be manually removed from the search results.
3. 'False-positive' documents which contain a keyword but have no relevance to the discovery request must also be manually eliminated.
4. Since choosing keywords is essentially a shot-in-the-dark approach, relevant documents which don't contain the specified keyword can be missed.
'Next Generation' conceptual search technology automates and broadens the search process, and is particularly valuable when working with large volumes of electronic data.
1. Employs mathematical algorithms to rapidly analyze entire document sets and identify relevant concepts and relationships.
2. Since conceptual search focuses on content, keyword issues such as alternative meanings or false-positives are eliminated; all documents containing similar concepts are readily identified.
3. With H&A's technology, users can submit phrases, paragraphs or entire documents as samples ('exemplars') of the concepts they wish to search for. As more exemplar documents are found and entered into the search parameters, the search results become increasingly focused.