Automated document harvesting and regenerating by crowdsourcing in enterprise social networks

Abstract

Various systems and methods are presented regarding automatically generating a document for a particular topic, and further utilizing an algorithm to automatically identify information in a resource that pertains to the topic. The document can be a purpose-specific document, created by a template configured to combine data fields to build the document. Each data field can be subject-matter specific with an associated algorithm. The algorithm can be trained to recognize and extract content that potentially meets the subject matter of the data field. The data field can be populated with the content. Subsequent editing of the content populating the data field can be monitored to determine an effectiveness of the algorithm to identify data of interest in the data repository. In the event of low success, the algorithm can be retrained. Further, the document can be regenerated if an algorithm is retrained, new information added to the repository, etc.