A Linear Temporal Logic Model Checking Method over Finite Words with Correlated Transition Attributes

Abstract

Temporal logic model checking techniques are applied, in a natural way, to the analysis of the set of finite traces composing a system log. The specific nature of such traces helps in adapting traditional techniques in order to extend their analysis capabilities. The paper presents an adaption of the classical Timed Propositional Temporal Logic to the case of finite words and considers relations among different attributes corresponding to different events. The introduced approach allows the use of general relations between event attributes by means of freeze quantifiers as well as future and past temporal operators. The paper also presents a decision procedure, as well as a study of its computational complexity.

Log-Based Session Profiling and Online Behavioral Prediction in E–Commerce Websites

“…The complete data (features along with the initial properties) from the clustering process was used to validate the clusters using model checking techniques [63]. To this end, this study proposes a set of validation queries related to results obtained from the clustering process.…”

“…Q 17 : How many sessions contain three or more PURCHASE events?) Table 5 shows the results obtained for each cluster (c i ), reflecting the percentage of sessions that the validation query (Q j ) fulfills with respect to the total number of sessions of the cluster, as well as the queries described in the LTL version proposed in [63]. In the table, operators G,F, and X have the usual LTL interpretation: Always, Eventually and Next, respectively, being H,O, and Y in past counterparts.…”