01583nam a2200217   4500000000100000008004100001260005700042653003400099653001800133653002700151653002400178653002100202653002500223100001400248700001600262700001300278245010400291490001300395520091500408020004201323                                       d  bSpringer Science and Business Media Deutschland GmbH10aAdaptive knowledge management10aEnriched maps10aGeographic Information10aMultimedia contents10aSemantic tagging10aTopic classification1 aM. Fugini1 aJ. Finocchi1 aE. Rossi00aSemantic Adaptive Enrichment of Cartography for Intangible Cultural Heritage and Citizen Journalism0 v438 LNNS3 aThe paper illustrates the basic features of a framework where knowledge is associated to geographic maps, to link geographical elements with geo and temporal-referenced contents. Among the key features, multimedia contents management and adaptivity to different application contexts are the most relevant. We propose a mixed approach to classify stored contents that combines natural language processing, based on a machine learning technique, with a human expert intervention. A dynamically configured user navigation is thereafter based on the classified contents and supported by a domain-specific ontology. Sample envisioned application areas are history, material and immaterial cultural heritage, architecture and urban planning, business intelligence, health, or citizen journalism. We provide some examples in the contexts of cultural heritage and journalism, which we are currently using as a testbed.  a23673370 (ISSN); 9783030980115 (ISBN)