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Database Tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical closeness of the multi-word technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT was used to obtain technical intelligence from a Fractals database derived from the Science Citation Index/Social Science Citation Index (SCI). Phrase frequency analysis by the technical domain experts provided the pervasive technical themes of the Fractals database, and the phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the Fractals literature supplemented the DT results with author/journal/institution publication and citation data.

Microblog can provide a valuable resource for journalists as it captures potential newsworthy events as they occur, including ones occurring remotely. Given the large volume and the fast pace of typical microblog, it is impractical to monitor all microblog postings for potential news events. Therefore, it would be useful if a method exists that uses text mining to help identify such events. For this endeavor, we need a good model of newsworthiness that furthermore can be operationalized with text-mining techniques. This study examines the feasibility and usefulness of such a model by first adopting the Shoemaker model of newsworthiness, one of the most comprehensive and accepted among such models; refining it based on a set of extensive interviews with domain experts and users in the context of news media in China; operationalizing it with a set of text-analytic measures in the domain of traffic accident; and testing its feasibility and validity using data from Weibo, the largest microblog site in China. As such, we believe that this study makes important theoretical and methodological contributions by developing and testing the most comprehensive and computable model of newsworthiness to date. We also point out its limitations and the areas that need further research.

Frugal innovations enable companies to access new markets because of some specific characteristics. Typically, they focus on existing solutions as a blueprint, changing parts of their functionality while reducing the costs. Many companies are faced with the question how to find ideas for such frugal innovations. For this purpose, we introduce a method for the identification of frugal invention candidates and their qualification as frugal patents. We provide a general outline of a process and apply it to the medical engineering technology. By use of semantic analysis, we shed light on the moderating role of frugal attributes to qualify a frugal invention candidate as a frugal patent. The application produces a comprehensive set of frugal patents. Our approach deepens the understanding of frugality by providing an appropriate assessment based on a newly developed frugal thesaurus. Managers will have the option to adapt our method to their particular fields of experience.