Abstract

In this study, we suggest the mobile business intelligence service based on adaptive recognition of user intention and usage patterns. This service is named as InSciTe adaptive and based on text mining and semantic web technologies. This service supports not only technology-focusing analysis and prediction but also adaptive recognition about user’s intention by semi-automatic user modeling process. By the adaptive user modeling, this service can provide more suitable service flow and more proper analysis results based on user’s intention.

Highlights

  • Mostafapour, 2012; Li et al, 2012; Cheung and Li, 2012)

  • We suggest the mobile business intelligence service based on adaptive recognition of user intention and usage patterns

  • This study is organized as follows: In section 2, we illustrate the user modeling for adaptive recognition of user intention and in section 3, we suggests an user grouping process based on user modeling results

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Summary

INTRODUCTION

Mostafapour, 2012; Li et al, 2012; Cheung and Li, 2012). the final objective of BI is precise. Business Intelligence (BI) is the ability of an organization to collect, maintain and organize knowledge This activity produces large amounts of information that can help in developing new opportunities. Several studies regarding BI have focused on technology analysis and predictions, such as Foresight and Understanding from Scientific Exposition (FUSE) DARPA, 2009, Combining and Uniting Business Intelligence with Semantic Technology (CUBIST) (Klai et al, 2012), Text Mining Software for Technology Management (Point, 2009). These projects aim to support decision making through analysis and pattern recognition of scientific information.

User Modeling
User Grouping
Technology Intelligence Services
CONCLUSION
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