Application of Big Data and Data Mining Techniques to Designing Building

Abstract

This study suggests an approach in designing new building, specifically a library with peer to peer social big data and survey data. Methods/Statistical analysis: Big data techniques such as social data mining, text mining, and association rule analysis are used in this study. This study uses sentiment analysis and opining mining in analyzing social data. Association rule analysis is used to understand the behavioral patter in survey data on daily movement of users in libraries. Findings: This study confirms that big data techniques such as social data mining, text mining, and association rule analysis can be efficiently applied to designing a building such as a library. Nouns related to library extracted from social media such as Twitter andblogs describe major services and facilities many people want in libraries. Adjectives from social data show that users’ feeling on the libraries. An analysis of data set from actual movement behaviors in the library shows efficient routing for library users. The study finds that data mash-up and big data techniques can help design new building, which is more efficient and convenient for users. Improvements/Applications: Designing a building using more advanced technique such as an artificial intelligence technique is possible with more diverse applications in design areas.