TECHNIQUES FOR DETECTING FILE SIMILARITY
개요
발명자
James Clark; Michael Slawinski
IPC 분류
CPC 분류
Techniques for detecting file similarity based on the characteristics and semantics of files are disclosed. A machine learning (ML) model may be trained to recognize and group files based on a hierarchy of file characteristics. The trained ML model may be used to process a set of files to generate a feature vector database comprising a set of feature vectors that are grouped based on the hierarchy of characteristics. In response to receiving a query file to be compared to the set of files, the ML model may be used to process the query file to generate a query feature vector. The query feature vector may be used to search the feature vector database to identify feature vectors that are similar to the query feature vector. A file corresponding to each feature vector that is similar to the query feature vector may be retrieved and presented to a user.
원문 (중국어)
Techniques for detecting file similarity based on the characteristics and semantics of files are disclosed. A machine learning (ML) model may be trained to recognize and group files based on a hierarchy of file characteristics. The trained ML model may be used to process a set of files to generate a feature vector database comprising a set of feature vectors that are grouped based on the hierarchy of characteristics. In response to receiving a query file to be compared to the set of files, the ML model may be used to process the query file to generate a query feature vector. The query feature vector may be used to search the feature vector database to identify feature vectors that are similar to the query feature vector. A file corresponding to each feature vector that is similar to the query feature vector may be retrieved and presented to a user.