Abstract: The significant increase in number of information sources unfavorable affects on traditional foresight techniques not directly adapted to big data era. Without automation of knowledge processing the quality of final foresight product is significally dependent on human (experts, analytics) abilities. In the article the new process workflow is proposed using text analytics tools to support all stages of foresight. The proposed advanced model of fact extraction with modified rules is based on new workflow, which includes marking data with additional metadata, using automated classification and sentiment extraction techniques, data quality improving steps in addition to quantitative and qualitative analysis of data. The modified rule based model of knowledge extraction adapted to used toolkit is presented. Given approach were tested on supporting of foresight process in domain of agricultural development of Crimea region.

Keywords: foresight, decision making, textual analytics, sentiment analysis, knowledge society, data mining, DSS.

ACM Classification Keywords: H.5.3 Group and Organization Interfaces - Computer-supported cooperative work

Link:

FORESIGHT PROCESS BASED ON TEXT ANALYTICS

Nataliya Pankratova, Volodymyr Savastiyanov

http://www.foibg.com/ijicp/vol01/ijicp01-01-p06.pdf