2015/02/21 by Dmytro Filatov, Filatov, Dmytro, Taras Filatov +1
Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #Biomedical Text Mining and Ontologies #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Information Retrieval (cs.IR) #Semantic Web and Ontologies #cs.AI #cs.IR
paper · pdf · doi:10.48550/arxiv.1502.06124
arxiv created 2015/02/21 · openalex publication_date 2015/02/21 · arxiv updated 2015/02/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
One of the most significant problems which inhibits further developments in the areas of Knowledge Representation and Artificial Intelligence is a problem of semantic alignment or knowledge mapping. The progress in its solution will be greatly beneficial for further advances of information retrieval, ontology alignment, relevance calculation, text mining, natural language processing etc. In the paper the concept of multidimensional global knowledge map, elaborated through unsupervised extraction of dependencies from large documents corpus, is proposed. In addition, the problem of direct Human - Knowledge Representation System interface is addressed and a concept of adaptive decoder proposed for the purpose of interaction with previously described unified mapping model. In combination these two approaches are suggested as basis for a development of a new generation of knowledge representation systems.