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Latent Semantic Search and Information Extraction Architecture

2019/11/30 by Anton Kolonin, Kolonin, Anton
Computer Science · #Artificial Intelligence (cs.AI) #Data Management and Algorithms #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Semantic Web and Ontologies #Web Data Mining and Analysis

paper · pdf · doi:10.48550/arxiv.1912.00180

openalex publication_date 2019/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The motivation, concept, design and implementation of latent semantic search for search engines have limited semantic search, entity extraction and property attribution features, have insufficient accuracy and response time of latent search, may impose privacy concerns and the search results are unavailable in offline mode for robotic search operations. The alternative suggestion involves autonomous search engine with adaptive storage consumption, configurable search scope and latent search response time with built-in options for entity extraction and property attribution available as open source platform for mobile, desktop and server solutions. The suggested architecture attempts to implement artificial general intelligence (AGI) principles as long as autonomous behaviour constrained by limited resources is concerned, and it is applied for specific task of enabling Web search for artificial agents implementing the AGI.

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