1. A method for knowledge extraction comprising: receiving data; identifying a process corresponding to the received data, the process being identified from a plurality of processes, the received data having a commonality with the process; identifying a knowledge of the process, the knowledge corresponding to the received data; determining categories of information for the received data utilizing the knowledge of the process; extracting information from the received data based on the categories of information, wherein extracting information from the received data generates extracted data; and creating records in a repository based on the extracted data, the records being adapted for use by a recommender, the recommender comprising a recommendation system.
1. A method for knowledge extraction comprising: receiving data; identifying a process corresponding to the received data, the process being identified from a plurality of processes, the received data having a commonality with the process; identifying a knowledge of the process, the knowledge corresponding to the received data; determining categories of information for the received data utilizing the knowledge of the process; extracting information from the received data based on the categories of information, wherein extracting information from the received data generates extracted data; and creating records in a repository based on the extracted data, the records being adapted for use by a recommender, the recommender comprising a recommendation system. 2. The method of claim 1 , wherein determining categories of information in the received data is based on a combination of the knowledge of the process and machine learning.