17. A method to identify a document, the method comprising: converting classified categories of recorded document data representing aspects of the recorded document data into a multi-dimensional vector signature, wherein each aspect provides a dimension of the multi-dimensional vector signature; determining uniqueness is high for the multi-dimensional vector signature by analysis of a term frequency of signatures within a specified distance of the multi-dimensional vector signature that indicates a number of similar multi-dimensional vector signatures within the specified distance is less than a specified value; using a hash of the multi-dimensional vector signature having high uniqueness as an address to data stored in a leaf node of a content database to access an associated signature at the leaf node of the content database; and correlating the associated signature with stored signatures obtained in a search of the content database to identify the document that was recorded.
17. A method to identify a document, the method comprising: converting classified categories of recorded document data representing aspects of the recorded document data into a multi-dimensional vector signature, wherein each aspect provides a dimension of the multi-dimensional vector signature; determining uniqueness is high for the multi-dimensional vector signature by analysis of a term frequency of signatures within a specified distance of the multi-dimensional vector signature that indicates a number of similar multi-dimensional vector signatures within the specified distance is less than a specified value; using a hash of the multi-dimensional vector signature having high uniqueness as an address to data stored in a leaf node of a content database to access an associated signature at the leaf node of the content database; and correlating the associated signature with stored signatures obtained in a search of the content database to identify the document that was recorded. 19. The method of claim 17 , wherein identification of a video clip is used along with other user and online website parameters to predict a user state or a user activity interest.