Why Vector Search Engine
Patent No. 7859641 granted / issued
Information Processing System and Method for Vectorizing Word Meanings and Searching Based on Vector Similarity
Conventional keyword matching and rule-based processing cannot capture "meaning" or "contextual proximity." This technology vectorizes words and sentences, placing them as numerical values in a multi-dimensional semantic space, absorbing ambiguity and polysemy while quantifying semantic proximity. This enables high-speed, high-accuracy extraction of information in the neighborhood of intent that conventional search would have missed.
Unlike conventional keyword search, this system retrieves similar cases based on semantic vector similarity and automatically extracts the reasons for that similarity.
Primary application scenarios:
Finance / Credit: Automatic extraction of decision rationale from past similar cases (combinable with Patent No. 7791512 for integrated loan decisioning and explanation generation)
Legal: Retrieval of similar precedents and contract clauses; extraction of grounds for verdict prediction
LLM Hallucination Mitigation: Tracing output rationale from similar documents (advanced RAG)
Vectorization is the advanced technology that makes meaning operable by converting language into numerical form — the foundation of next-generation AI communication.