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Current studies on software development either focus on the change history of source code from version-control systems or on an analysis of simplistic in-IDE events without context information. Each of these approaches contains valuable information that is unavailable in the other case. Our work proposes enriched event streams, a solution that combines the best of both worlds and provides a holistic...
We present a general computational narrative model encompassing primitives of space, time, and motion from the viewpoint of deep knowledge representation and reasoning about visuo-spatial dynamics, and (eye-tracking based) visual perception of the moving image. The declarative model, implemented within constraint logic programming, integrates knowledge-based qualitative reasoning (e.g., about object...
We adapt the 'mosaics' technique of Reynolds 1997 (in turn an adaption of Németi 1986) achieving decidability for the (non local) Ockhamist logic of (upward endless) bundled trees. We produce a double exponential time procedure, thus improving the complexity upper bound of the problem - so far relying on the non elementary procedure of the Rabin's Theorem (Burgess 1979).
Process mining algorithms use event logs to learn and reason about processes by technically coupling event history data and process models. During the execution of a learning process, several events occur which are of interest and/or necessary for completing and achieving a learning goal. The work in this paper describes a Semantic Process Mining approach directed towards automated learning. The proposed...
This paper is a reflection on how video games support representations of history by using the interactive particularities of the medium. History appears as a space that can be recreated through technologically-mediated performances in which players are assigned the role of participants in a story made available by design. Fiction and realism are constitutive parts of historical games in which players...
Provenance awareness adds a new dimension to the engineering of service-based systems, enabling them to increase their accountability through answering questions about the provenance of any data produced. Provenance awareness can be achieved by recording provenance data during system execution. In our previous work we have proposed an overall research agenda towards a design and analysis framework...
This paper presents Comme il Faut (CiF), an artificial intelligence system that matches character performances to appropriate social context, with the goal of enabling authors to write high-level rules governing expected character behavior in given social situations, rather than specific fixed choice points in a curated narrative structure. CiF models characters with a complex set of traits, feelings,...
Context-aware systems provide proactive services for users based on environment contexts reasoning. This paper proposes context-aware systems, and addresses the important issues of modeling and evolutionary context rules. Service modeling is based on ontology technology to describe context-aware systems, and service reasoning rules are constantly extracted and evolved using tough-set theory by accommodating...
Situation-aware case-based decision support (SACBDS) systems comprise two distinct parts: situation awareness (SA) and case-based reasoning (CBR). The SA part keeps a finite history of the time space information of the domain and uses rules to interpret cues from the environment with respect to an individual user's context, and then anticipates future situations by performing statistical inference...
In a dynamic and heterogeneous world as the Web, the need often arises to update XML data, as well as their structures, to adhere to new domain requirements. Updates may break compliance of data to schemas, and updates at schema level may in addition require to adapt associated documents to the new schema. Moreover, emerging application contexts in which updates come from different sources, such as...
Context is an important factor for the success of dynamic service composition. Although many context-based AI or workflow approaches have been proposed to support dynamic service composition, there is still an unaddressed issue of the support of fine-granularity context management. In this paper, we propose a granularity-based context model together with an approach to supporting the intelligent context-aware...
Context-awareness is a key issue for future applications within heterogeneous and networked environments. In terms of efficiency and reusability, such applications should be separated from the problems of context gathering and modeling, but should instead profit from and contribute to cross-application context information. For this purpose, an ontology-based, cross-application context modeling and...
Semantic category theory indicates that human thinking involves four, entirely distinct types of information processing, each associated with a totally independent dasiasemantic categorypsila. However, observation also indicates that human cognition does not enforce strong data typing. Whilst this enables the creation of beautiful poetry and prose, weak data typing can also lie at the heart of persuasive...
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