Modelling a Query Space Using Associations

摘要: We all use our associative memory constantly. Words and concepts form paths that we can follow to find new related concepts; for example, when think about a car may associate it with driving, roads or Japan, country produces cars. In this paper present an approach information modelling is derived from human memory. The idea create network of where the links model strength association between instead of, semantics. network, called be learned unsupervised learning algorithm using concept co-occurrences, frequencies distances. possibility brings great benefit compared semantic networks, ontology development usually requires lot manual labour. case associations bring benefits over semantics due easier implementation overall concept. focuses on business intelligence search engine modelled its query space modelling. utilised in retrieval system development.