دانلود مقاله ISI انگلیسی شماره 44371
ترجمه فارسی عنوان مقاله

شناسایی سیگنال ضعیف با معدن وب معنایی

عنوان انگلیسی
Weak signal identification with semantic web mining
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
44371 2013 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 40, Issue 12, 15 September 2013, Pages 4978–4985

چکیده انگلیسی

We investigate an automated identification of weak signals according to Ansoff to improve strategic planning and technological forecasting. Literature shows that weak signals can be found in the organization’s environment and that they appear in different contexts. We use internet information to represent organization’s environment and we select these websites that are related to a given hypothesis. In contrast to related research, a methodology is provided that uses latent semantic indexing (LSI) for the identification of weak signals. This improves existing knowledge based approaches because LSI considers the aspects of meaning and thus, it is able to identify similar textual patterns in different contexts. A new weak signal maximization approach is introduced that replaces the commonly used prediction modeling approach in LSI. It enables to calculate the largest number of relevant weak signals represented by singular value decomposition (SVD) dimensions. A case study identifies and analyses weak signals to predict trends in the field of on-site medical oxygen production. This supports the planning of research and development (R&D) for a medical oxygen supplier. As a result, it is shown that the proposed methodology enables organizations to identify weak signals from the internet for a given hypothesis. This helps strategic planners to react ahead of time.