Vector-Based File Search Engine for Contextual Tagging

The patent transforms the search matching process from traditional text-based comparison to vector-based spatial comparison. Words and context data are converted into vectors with spatial coordinates, and the matching accuracy is improved by calculating the theta angle between search vectors and file vectors. This parameter transformation enables the system to capture semantic relationships and user context, significantly improving search relevance while maintaining computational efficiency through standardized vector operations.

The patent implements a two-stage processing approach where vectors for words and context data are pre-calculated and stored in a lookup table before the actual search operation. During search execution, the system only needs to retrieve pre-computed vectors and perform relatively simple theta angle calculations between search vectors and file vectors. This preliminary action significantly reduces the computational burden during real-time search operations while maintaining high matching precision.

The patent introduces vector representations as an intermediary layer between the search query and the file descriptors. Instead of directly trusting or rejecting arbitrary text descriptors, the system converts both the search terms and the file descriptors into vectors and compares their spatial relationships. This intermediary vector-based comparison method objectively assesses the relevance between search intent and file content, reducing reliance on potentially misleading arbitrary descriptors while maintaining system simplicity.