The paper introduces and discusses the notion of decomposition of a configuration problem within the framework of a structured logical approach. The paper describes under which conditions a given configuration problem can be decomposed into a set of noninteracting subproblems and how to exploit such a decomposition, both for improving the performance of the configurator and for supporting interactive configuration. Different kinds of decomposition are considered, but all of them exploit, as much as possible, the explicit representation of the partonomic relations in the FPC language, a KL-One like representation formalism augmented with constraints for expressing complex interrole relations. The paper introduces a notion of boundness among constraints, which is used for formally specifying different types of decomposition. One decomposition strategy aims at singling out the components and subcomponents that are directly related to the constraints put by the user's requirements; the configurator exploits such decomposition by first configuring that portion of the product and then configuring the parts that are not related to the user's requirements. Another decomposition strategy verifies whether the set of constraints for the product to be configured can be split into a set of noninteracting problems. In such a case the configurator solves the configuration problem by splitting the whole search space into a set of smaller search spaces. Different combinations of these two decomposition techniques are considered, and the impact of the decomposition strategies on the performance of the configurator is evaluated via a set of experiments using the configuration of computer systems as a test bed. The results of the experiments show a significant reduction of the computational effort~both in terms of number of backtrackings and in CPU time! when decomposition strategies are used.
In this paper we discuss the issues related to the formal representation of thematic roles in an ontology modeling historical events. We start by analyzing the ontological distinctions between thematic roles and social roles, which suggest different formal representations. Coupling the study of existing approaches with an analysis of historical texts available within the Harlock'900 project we propose a formal representation of thematic roles in HERO (Historical Event Representation Ontology), based on binary properties, directly connecting the event to its participants. Moreover, we show that a fine-grained formal ontological model of participation in (historical) events should include general thematic roles (e.g., agent, patient) able to capture the common aspects of the ways entities are involved in events and event-specific roles (e.g., sniper), introduced in the ontology according to a specific criterion, that guarantees the needed expressivity without proliferating roles. We conclude the paper by discussing the benefits of our approach.
Historical archives represent an immense wealth, the potential of which is endangered by the lack of effective management and access tools. We believe that this issue can be faced by providing archive catalogs with a semantic layer, containing rich semantic metadata, representing the content of documents in a full-fledged formal machine-readable format. In this paper we present the contribution offered in this direction by the PRiSMHA project, in which the conceptual vocabulary of the semantic layer is represented by computational ontologies. However, acquiring semantic knowledge represents a well-known bottleneck for knowledge-based systems: in order to solve this problem, PRiSMHA relies on a crowdsourcing collaborative model, i.e., an online community of users who collaborate in building semantic representations of the content of archival documents. In this perspective, this paper aims at answering the following research question: Starting from the axioms characterizing concepts in the computational ontology underlying the system, how can we derive a user interface enabling users to formally represent the content of archival documents by exploiting the conceptual vocabulary provided by the ontology? Our solution includes the following steps: (a) A manually defined configuration, acting as a pre-filter, to hide "unsuited" classes, properties, and relations; (b) An algorithm, combining heuristics and reasoning, which extracts from the ontology all and only the "compatible" properties and relations, given an entity (event) type. (c) A set of strategies to rank, group, and present the entity (event) properties and relations, based on the results of a study with users. This integrated solution enabled us to design an ontology-driven user interface enabling users to characterize entities, and in particular (historical) events, on the basis of the vocabulary provided by the ontology.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.