Abstract | ||
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The change in technological environment presents threats as well as opportunities to companies in the related fields. Existing Technology Intelligence procedures require complicated techniques and high-skilled labor results. Large expert-interviews and manual work is also needed, so single small companies can not undertake this alone. To spread and activate Technology Intelligence in research and industrial fields, we propose shallow, but automated, Technology Intelligence services based on Semantic Web technologies, which can reduce the amount of labor required from experts. We explain our Semantic Web technologies, such as ontology modeling, semantic repository, inference and verification and how they make our Technology Intelligence services possible. |
Year | DOI | Venue |
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2011 | 10.1007/978-3-642-23620-4_35 | AMT |
Keywords | Field | DocType |
technology intelligence,semantic web technology,manual work,industrial field,technology intelligence service,ontology modeling,technology intelligence procedure,complicated technique,large expert-interviews,high-skilled labor result | Data science,Data mining,World Wide Web,Semantic technology,Technology intelligence,Web intelligence,Semantic Web Stack,Computer science,Semantic Web,Semantic analytics,Social Semantic Web,Semantic computing | Conference |
Citations | PageRank | References |
2 | 0.44 | 1 |
Authors | ||
8 |
Name | Order | Citations | PageRank |
---|---|---|---|
Seungwoo Lee | 1 | 366 | 42.33 |
Mikyoung Lee | 2 | 55 | 12.56 |
Hanmin Jung | 3 | 293 | 55.28 |
Pyung Kim | 4 | 129 | 11.64 |
Dongmin Seo | 5 | 49 | 10.64 |
Tae Hong Kim | 6 | 2 | 0.44 |
Jinhee Lee | 7 | 80 | 21.11 |
Won-Kyung Sung | 8 | 145 | 19.93 |