Abstract: A method and apparatus for partitioning high-dimension vectors for use in a massive index have been disclosed. Using an initial guess on a collection of vectors, the vectors are examined. If the collection is not empty then dividing the collection until a collection contains a single vector or contains two vectors then transforming the two vectors into a majorize result and transforming the result into a graphical representation for a user.

Abstract: A method and apparatus for cached adaptive transforms for compressing data streams, computing similarity, and recognizing patterns have been disclosed. In one embodiment of the invention an encoder and decoder begin with a baseline transform. As data is transferred an algorithm is arranged so that the encoder and decoder adapt toward a superior basis than the baseline, with a corresponding reduction in the encoding bit rate. That is the algorithm adapts to the incoming data stream and can use a custom basis. We deliberately avoid having to send the custom basis itself (when possible), because sending the basis vectors consumes precious bandwidth and may defeat the goal of compression. The encoder and decoder can bootstrap themselves into using one or more better bases. In one embodiment of the invention there is no beginning baseline transform shared between the encoder and the decoder.

Abstract: A method and apparatus for fast similarity-based query, self-join, and join for massive, high-dimension datasets have been disclosed.

Abstract: A method and apparatus for efficient indexed storage for unstructured content have been disclosed.

Abstract: A method and apparatus for efficient indexed storage for unstructured content have been disclosed.

Abstract: A method and apparatus for cached adaptive transforms for compressing data streams, computing similarity, and recognizing patterns have been disclosed. In one embodiment of the invention an encoder and decoder begin with a baseline transform. As data is transferred an algorithm is arranged so that the encoder and decoder adapt toward a superior basis than the baseline, with a corresponding reduction in the encoding bit rate. That is the algorithm adapts to the incoming data stream and can use a custom basis. We deliberately avoid having to send the custom basis itself (when possible), because sending the basis vectors consumes precious bandwidth and may defeat the goal of compression. The encoder and decoder can bootstrap themselves into using one or more better bases. In one embodiment of the invention there is no beginning baseline transform shared between the encoder and the decoder.

Abstract: A method and apparatus for efficient indexed storage for unstructured content have been disclosed.

Abstract: A method and apparatus for partitioning high-dimension vectors for use in a massive index tree have been disclosed.

Abstract: A method and apparatus for cached adaptive transforms for compressing data streams, computing similarity, and recognizing patterns have been disclosed. In one embodiment of the invention an encoder and decoder begin with a baseline transform. As data is transferred an algorithm is arranged so that the encoder and decoder adapt toward a superior basis than the baseline, with a corresponding reduction in the encoding bit rate. That is the algorithm adapts to the incoming data stream and can use a custom basis. We deliberately avoid having to send the custom basis itself (when possible), because sending the basis vectors consumes precious bandwidth and may defeat the goal of compression. The encoder and decoder can bootstrap themselves into using one or more better bases. In one embodiment of the invention there is no beginning baseline transform shared between the encoder and the decoder.

Abstract: A method and apparatus for efficient indexed storage for unstructured content have been disclosed.

Abstract: A method and apparatus for fast similarity-based query, self-join, and join for massive, high-dimension datasets have been disclosed.

Abstract: A method and apparatus for fundamental operations on token sequences: computing similarity, extracting term values, and searching efficiently have been disclosed.

Abstract: A method and apparatus for fundamental operations on token sequences: computing similarity, extracting term values, and searching efficiently have been disclosed.

Abstract: A method and apparatus for fast similarity-based query, self-join, and join for massive, high-dimension datasets have been disclosed.

Abstract: A method and apparatus for efficient indexed storage for unstructured content have been disclosed.

Abstract: A method and apparatus for cached adaptive transforms for compressing data streams, computing similarity, and recognizing patterns have been disclosed.

Abstract: A method and apparatus for information factoring have been disclosed by representing a source information asset as a point in a metric space and rendering said source information asset in a second form.

Abstract: A method and apparatus for fundamental operations on token sequences: computing similarity, extracting term values, and searching efficiently have been disclosed.