Abstract

PEREZ PUPO, Iliana et al. Discovering linguistic summaries for help in project management decisions.. Rev cuba cienc informat [online]. 2018, vol.12, suppl.1, pp.163-175. ISSN 2227-1899.

The linguistic data summarization consists on data mining techniques used to discover intrinsic relationships present in the data. These techniques generate linguistic summaries from discovered relationships. There are different algorithms to generate summaries, the simplest summaries con be generated by using standard query languages. Other authors built summaries by using metaheuristics such as genetic algorithms. This paper presents a new linguistic data summarization techniques based on combination of algorithms to generate association rules, fuzzy logic and active learning. Summaries are evaluated by a combination of T values proposed by Zadeh and active learning techniques. Finally, the proposed technique is applied in project management context. The paper discusses different decisions taken form linguistic summaries.

Keywords : association rules; degree of truth; linguistic data summarization; project management.

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