Converting a Historical Architecture Encyclopedia into a Semantic Knowledge Base

IEEE Intelligent Systems(2010)

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摘要
Digitizing a historical document using ontologies and natural language processing techniques can transform it from arcane text to a useful knowledge base.The Handbook on Architecture (Handbuch der Architektur) was perhaps one of the most ambitious publishing projects ever. Like a 19thcentury Wikipedia, it attempted nothing less than a full account of all architectural knowledge available at the time, both past and present. It covers topics from Greek temples to contemporary hospitals and universities; from the design of individual construction elements such as window sills to large-scale town planning; from physics to design; from planning to construction. It also discusses architectural history and styles and a multitude of other topics, such as building conception, statics, and interior design.Not surprisingly, this project took longer than planned. The encyclopedia's first volume was partly published in 1880, and over the next 63 years more than 100 architects worked on what would become more than 140 individual publications with over 25,000 pages. One important insight of our work is that targeted text analysis support, already available today, can easily be integrated into common desktop tools to support users for their task at hand. While NLP techniques are far from perfect or comprehensive, they can already deliver knowledge discovery support that goes significantly beyond the currently used approach of full-text search and information retrieval.
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deductive databases,encyclopaedias,information retrieval,knowledge based systems,ontologies (artificial intelligence),text analysis,NLP techniques,architectural knowledge,historical architecture encyclopedia,historical document,information retrieval,language processing techniques,large scale town planning,ontologies,semantic knowledge base,text analysis support,Handbook on Architecture,Handbuch der Architektur,cultural heritage data management,knowledge base management,natural language processing,ontologies,ontology population,semantic Wiki,text mining
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