With the proliferation of computing devices, as well as of information technologies, a variety of domain-specific information processing paradigms has appeared in different application domains including signal/image processing, system modelling, machine learning, data mining, knowledge representation, pattern analysis, logic and reasoning, symbol manipulation, etc. The corresponding mathematical tools are, frequently, different also due to the need to cope with disparate types of data including, in particular, matrices of real numbers, (cumulative) functions, sets/partitions, information granules, logic values, data structures/relations, strings of symbols, etc. A unification of the aforementioned tools is expected to result in a fruitful cross-fertilization of technologies. However, what is currently missing is an “enabling” mathematical framework.


V.G. Kaburlasos (Guest Editor), Special Issue on: Information Engineering Applications Based on Lattices, Information Sciences, vol. 181, iss. 10, pp. 1771-1773, 2011 (16 papers, pp. 1774-2060).