502 research outputs found
GSO: Designing a Well-Founded Service Ontology to Support Dynamic Service Discovery and Composition
A pragmatic and straightforward approach to semantic service discovery is to match inputs and outputs of user requests with the input and output requirements of registered service descriptions. This approach can be extended by using pre-conditions, effects and semantic annotations (meta-data) in an attempt to increase discovery accuracy. While on one hand these additions help improve discovery accuracy, on the other hand complexity is added as service users need to add more information elements to their service requests. In this paper we present an approach that aims at facilitating the representation of service requests by service users, without loss of accuracy. We introduce a Goal-Based Service Framework (GSF) that uses the concept of goal as an abstraction to represent service requests. This paper presents the core concepts and relations of the Goal-Based Service Ontology (GSO), which is a fundamental component of the GSF, and discusses how the framework supports semantic service discovery and composition. GSO provides a set of primitives and relations between goals, tasks and services. These primitives allow a user to represent its goals, and a supporting platform to discover or compose services that fulfil them
Attempto Controlled English (ACE)
Attempto Controlled English (ACE) allows domain specialists to interactively
formulate requirements specifications in domain concepts. ACE can be accurately
and efficiently processed by a computer, but is expressive enough to allow
natural usage. The Attempto system translates specification texts in ACE into
discourse representation structures and optionally into Prolog. Translated
specification texts are incrementally added to a knowledge base. This knowledge
base can be queried in ACE for verification, and it can be executed for
simulation, prototyping and validation of the specification.Comment: 13 pages, compressed, uuencoded Postscript, to be presented at CLAW
96, The First International Workshop on Controlled Language Applications,
Katholieke Universiteit Leuven, 26-27 March 199
Enrichment of raw sensor data to enable high-level queries
Sensor networks are increasingly used across various application domains. Their usage has the advantage of automated, often continuous, monitoring of activities and events. Ubiquitous sensor networks detect location of people and objects and their movement. In our research,
we employ a ubiquitous sensor network to track the movement
of players in a tennis match. By doing so, our goal is to create a detailed analysis of how the match progressed, recording points scored, games and sets, and in doing so, greatly reduce the eort of coaches and players who are required to study matches afterwards. The sensor network
is highly efficient as it eliminates the need for manual recording of the match. However, it generates raw data that is unusable by domain experts as it contains no frame of reference or context and cannot be analyzed or queried. In this work, we present the UbiQuSE system of data transformers which bridges the gap between raw sensor data and the high-level requirements of domain specialists such as the tennis coach
Ontology based Clinical Practice Justification in Natural Language
One of the most important contributions that any decision
support system can make to achieve wide acceptance among any community
is to be able to justify its own suggestions. When dealing with highly
technical and scientifically advanced practitioners like medical
doctors or any other related clinical workers, the ability to justify
itself using the domain specialist usual terminology and technicalities
is imperative. In this article we demonstrate the use of an ontological
framework as inferencing basis for automatic sound clinical suggestions
providing. Our work has two main contributions, consolidating the
use of \{OGCP\} (Ontology for General Clinical Practice) as foundation
and providing controlled English justifications of the extracted
suggestions. We found that clinical practitioners feel as acceptable
the Attempto Controlled English justifications generated from the
knowledge base
How Digital Cultural Heritage Resources can Lead to New Understandings in the Humanities: Future Challenges for Digital Libraries and Archives (Invited Paper)
This paper reports on the presentation made during the panel on "Digital Libraries and Digital Archives: Problems and Challenges for AI Approaches" of the 1st Workshop on Intelligent Techniques At LIbraries and Archives (ITALIA 2015) co-located with the XIV Conference of the Italian Association for Artificial Intelligence, 22 September 2015, Ferrara, Italy
Knowledge Organization Research in the last two decades: 1988-2008
We apply an automatic topic mapping system to records of publications in
knowledge organization published between 1988-2008. The data was collected from
journals publishing articles in the KO field from Web of Science database
(WoS). The results showed that while topics in the first decade (1988-1997)
were more traditional, the second decade (1998-2008) was marked by a more
technological orientation and by the appearance of more specialized topics
driven by the pervasiveness of the Web environment
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