On Generating Stories from Semantically Annotated Tourism-Related Content

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11230)


In online marketing communication, publication consistency and content diversity are two important factors for marketing success. Especially in the tourism industry, having a strong online presence through the dissemination of high-quality content is highly desired. A method to maintain these two factors is by collecting and remixing various user-generated contents available on the Web and presenting them more interestingly. This method, known as content curation, has been widely used in social media. Multiple social media content can be aggregated for further consumption, for instance by listing them in historical order or grouping them according to particular topics. While the amount of user-generated content available on the Web is continuously increased, finding and selecting content to be mixed into a meaningful story are mainly performed manually by humans. These are challenging tasks due to the vast amount of accessible content on the Web, presented in various formats, and available in distributed sources. In this paper, we propose a method to automatically generate stories in the tourism industry by leveraging rule-based system over a collection of semantically annotated content. The method utilizes data dynamics of annotations, detected through a rule-based system, to identify the relevant content to be selected and mixed. We evaluated our method with a collection of semantically annotated tourism-related content from the region of Tyrol, Austria with promising results.


Semantic annotation Automatic story generation Rule-based system Online marketing Tourism marketing 



We would like to thank all the members of the Online Communication working group ( of the Semantic Technology Institute (STI) Innsbruck for their valuable feedback and suggestions. The work is partially supported by the Indonesian Institute of Sciences (


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Research Center for InformaticsIndonesian Institute of SciencesCibinongIndonesia
  2. 2.Semantic Technology Institute (STI) Innsbruck, University of InnsbruckInnsbruckAustria

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