This paper proposed a Sequential pAttern Mining mOdel (SAMO) for discovering critical links and evaluating road importance in transportation systems. SAMO introduces novel criticality indices derived from association rule mining and data analysis of vehicular trajectory data. These indices are designed to assess the criticality of road links within a network by leveraging mining frequent patterns and extract meaningful associations from the trajectory data. SAMO prioritizes links that feature prominently in frequent trajectory patterns, with additional weight given to patterns with high confidence levels. We evaluated the performance of our indices within machine learning prediction models alongside with the traditional indices used in the literature. Our results demonstrate that integrating our proposed indices improves prediction accuracy across various models, with the indices consistently ranking among the top features. This indicates the promising potential of our indices for evaluating and assessing critical links in transportation networks.

We report a corrected version of the algorithms to compute ternary projective relations between regions appeared in E. Clementini and R. Billen, "Modeling and computing ternary projective relations between regions," IEEE Transactions on Knowledge and Data Engineering, vol. 18, pp. 799-814, 2006.

This paper introduces a reasoning system based on a previously developed model for ternary projective relations between spatial objects. The model applies to spatial objects of the kind point and region is based on basic projective invariants and takes into account the size and shape of the three objects that are involved in a relation. The reasoning system proposes a set of permutation and composition rules, which allow the inference of unknown relations from given ones.

Current spatial database systems offer limited querying capabilities beyond binary topological relations. This paper introduces a model for projective relations between regions to support other qualitative spatial queries. The relations are ternary because they are based on the collinearity invariant of three points under projective geometry. The model is built on a partition of the plane into separate zones that are obtained from projective properties of two reference objects: then, by considering the empty/nonempty intersections of a primary object with these zones, the model is able to distinguish between 34 different projective relations. Then, the paper proposes original algorithms for computing the relations under the assumption that regions of the plane are stored as vector polygons in a spatial database. These algorithms run in optimal O(nlogn) time