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Title: The framework of discovery early adopters’ incipient innovative ideas
Authors: 林木花
Hong, Chao Fu
Lin, Mu Hua
Lin, Woo Tsong
Contributors: 資管系
Keywords: Database systems;Internet;Association analysis;Business service;Business success;Chance discovery;Innovation diffusion;Innovative ideas;Social influence;Term Frequency;Inverse problems
Date: 2016
Issue Date: 2017-09-01 10:06:10 (UTC+8)
Abstract: Crossing the chasm between early adopters and early majority in the market is not only an important issue for innovation diffusion, but also important information for firms to have the chance to occupy position and get great business success. Additionally, consumers can easily share their consumer-related articles through various IT blogs with Web 2.0, hence there is a big consuming data on the Internet. This research tried to discover incipient innovative ideas from early adopters to help firms to win the business. A new textual association analysis (Term Frequency - Inverse Clusters Frequency, TF-ICF) framework is a methodology to discover the more rare and useful ideas for designing future innovative business service. In the present study, TF-ICF methodology does not only find what instant foods or entertainment are needed for the passengers on travelling vehicles, but also reveal that the moisturizing emulation is another possible need of theirs. The results show that the TF-ICF method is useful to discover early adopters’ incipient innovative ideas.
Relation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9622, 319-327
Data Type: conference
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Appears in Collections:[資訊管理學系] 會議論文

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