By my definition, Talent Mining is a simple adaptation of Data Mining, which according to Wikipedia is the process of sorting through large amounts of data and picking out relevant information, or “the nontrivial extraction of implicit, previously unknown, and potentially useful information from data” and “the science of extracting useful information from large data sets or databases.”
I define Talent Mining as the science of sorting through large amounts of human capital/talent-related data, typically found in resume databases, on the Internet, in social networking profiles, blog posts, etc., and extracting out relevant and useful information from the data that can be used for talent identification and acquisition.
Talent Mining is commonly performed manually and automatically, through the creation and execution (or saving for routine execution, as in the case of search agents or alerts) of Boolean search strings to retreive human capital/talent data from which a recruiter can use for knowledge discovery and talent identification and acquisition.
True Talent Mining goes well beyond “buzzword matching,” and in the hands of an expert Talent Miner, Boolean search strings can be used to perform Semantic Search – using semantics, or the science of meaning in language to produce highly relevant search results – even from unstructured data. How’s THAT for sexy?
Look for a post on Semantic Search coming soon.