1436959
Towards Semantically Grounded Decision Rules Using ORM +
Recently, ontologies are proposed for many purposes to assist decision making, such as representing terminology and categorizing information. Current ontology-based decision support systems mainly contain semantically rich decision rules. In order to ground the semantics, we formalize those rules by committing them to domain ontologies. Those semantically grounded decision rules can represent the semantics precisely, thus improve the functionalities of many available rule engines. We model and visualize the rules by means of a novel extension of ORM. These rules are further stored in an XML-based markup language, ORM+ ML, which is a hybrid language of Rule-ML and ORM-ML. We demonstrate in the field of on-line customer management.
31156520
An Ontology-based Data Matching Framework: use Case Competency-based HRM
As part of the European PROLIX (Process Oriented Learning and Information eXchange) project, VUB STARLab designed a generic ontology-based data matching framework (ODMF). Within the project, the ODMF is used to calculate the similarity between data elements, e.g. competency, function, person, task, and qualification, based on competency-information. Several ontology-based data matching strategies were implemented and evaluated as part of the ODMF. In this article we describe the ODMF and discuss the implemented matching strategies.
32294667
Use Semantic Decision Tables to Improve Meaning Evolution Support Systems
Meaning Evolution Support Systems have been recently introduced as a real-time, scalable, community-basedcooperative systems to support the ontology evolution. In this paper, we intend to address the problems of accuracyand effectivenessin Meaning Evolution Support Systems in general. We use Semantic Decision Tables to tackle these problems. A Semantic Decision Table separates general decision rules from the processes, bootstraps policies and template dependencies in the whole system. Recently, DOGMA-MESS (" D eveloping O ntology G rounded M ethodology and A pplications" framework based " M eaning E volution S upport S ystems") is developed at VUB STARLab as a collection of meaning evolution support systems. We embed Semantic Decision Tables in DOGMA-MESS to illustrate our approach. Semantic Decision Tables play the roles in both top-downand bottom-upprocesses of the meaning evolution cycle. The decision rules that consist of templates dependency rules are mainly responsible for the top-down process execution. The bottom-up process execution relies on the ones that contain the concept lifting algorithms.
33017168
An ontology engineering methodology for DOGMA
Although ontologies occupy a central place in the Semantic Web and related research domains, there are currently not many fully fledged ontology engineering methodologies available. In this paper, we want to present an integrated methodology for ontology engineering from scratch, inspired by various scientific disciplines, in particular database semantics and natural language processing.
17885523
On Constructing Semantic Decision Tables
Decision tables are a widely used knowledge management tool in the decision making process. Ambiguity and conceptual reasoning difficulties arise while designing large decision tables in a collaborative environment. We introduce the notion of Semantic Decision Table (SDT), which enhances a decision table with explicit decision semantics by annotating it properly with a domain ontology. In this paper, we focus on the SDT construction process. First, we map decision items to the ontology by building a rooted tree of decision binary facts and visualize it in a scalable manner. Formal ontological roles are used during this mapping process. Then, we commit the decision rules to the mapping results with a high level pseudo-natural language to ground their semantic. We illustrate with an SDT example from the domain of human resource management.
2555681
Judicial Support Systems: Ideas for a Privacy Ontology-Based Case Analyzer
Nowadays, ontology is applied as an integral part of many applications in several domains, especially in the world of law. The ontology based judicial support system is believed as a useful tool to support, for example, the legal argumentation assistant and legal decision taking in court. The privacy case analyzer is considered as one of the most interesting applications of ontology based privacy judicial support systems. The efficiency of privacy case analyzers depend on several factors such as how to tackle the problem of linking cases to legislations, how to imply the guidance of privacy principles, and how to improve the extraction of cases. This paper addresses those items and describes the research issues that will be investigated challenges of ontology based judicial support systems.
1301888
Auction-Based Resource Reservation Game in Small World
For read-only storages and in particular for PLA applications, improved coupling elements together with an associated personalization scheme permit the storing of at least two memory (or logic) connection patterns selectable independently of each other. Quick electrical switching between at least two functional modes in the same storage array, is also provided. One device field effect transistor (FET) cells with specific gate configurations depending on the respective personalization state are used as coupling elements. For instance, in a two-fold personalization permanent storage, the coupling elements consist of FETs with two gate sections provided one beside the other. For a connection to be established in only one of the two possible functions at the respective crosspoint, one of the gate sections is connected to the control line provided for the functional selection. The remaining gate section is connected to the associated input line. A connection in the other functional mode is provided correspondingly with only the control lines being switched. If at the respective crosspoint a connection is to be effective in both functional modes, both gate sections are jointly connected to the respective input line. By using only one common peripheral circuit, PLAs with multiple personalization properties can be made in integrated technology, with the same semiconductor area requirement as PLAs personalizable into only one functional mode.
44335940
DRC-BK: Mining Classification Rules with Help of SVM
Currently, the accuracy of SVM classifier is very high, but the classification model of SVM classifier is not understandable by human experts. In this paper, we use SVM, which is applied with a Boolean kernel, to construct a hyper-plan for classification, and mine classification rules from this hyper-plane. In this way, we build DRC-BK, a decision rule classifier. Experiment results show that DRC-BK has a higher accuracy than some state-of-art decision rule (decision tree) classifiers, such as C4.5, CBA, CMAR, CAEP and so on.
9189850
The Parameter Optimization of Human-Simulated Intelligent Controller Based on Improved Genetic Algorithm
The human-simulated intelligent controller, using a hierarchical and multi-mode control structure, effectively solves the control difficult problems of many complex systems. But there are many parameters to be determined. In order to solve them, the paper introduces an improved genetic algorithm (IGA) which is combined with orthogonal design method. It is served as the simulation experiment platform by the cart-double pendulum. Through selected the reasonable fitness function and determined the appropriate parameters range, using the IGA, the parameters of the human-simulated intelligent controller are optimized. The simulation results show the IGA is better than the manual adjustment method. So it is proved that the IGA is more effective in solving the parameter optimization of human-simulated intelligent controller, and also promotes the more extended application space of intelligent control theory.
17461739
The design and implementation of LilyTask in shared memory
Constructing high performance computing system and providing easy-to-use programming model for users are two main parts of parallel computing, but the latter has been in a sorry state for a long time. LilyTask programming model is based on tasks which can be easily mapped to the decomposition of computation. Without explict synchronization and mutual exclusion, users will concentrate on the inherent parallelism in a problem instead of lock/unlock programming techniques. Most existing implementations of the task pool, a flexible data structure for task parallel, lack basic representation of relations among tasks. LilyTask introduces task group and task relation to help users easily map subproblems to tasks. The kernel of LilyTask system, a distributed task pool, automatically exploits potential parallelism among tasks at runtime. With runtime task assignment and task stealing, LilyTask system achieves dynamic load balancing. Our performance evaluation shows that LilyTask system with task pool outperforms sequential programs and BSPlib in solving both regular and irregular problems.
40790501
A Practical Peer-Performance-Aware DHT
How to Build an efficient Distributed Hash Table (DHT) is a fundamental issue in Peer-to-Peer research field. Previous solutions ignore the heterogeneity of the large scale network. However, in practice, the fact is that the resource held by each peer in the Internet is extremely diverse. And the the willing to share local resources of each peer is also diverse. Therefore, the contribution for the system of a peer should depend on the resources it holds or how many resources it want to share, and should not be uniform. In this paper, we propose a Peer-Performance-Aware Distributed Hash Table (PPADHT) which aims to exploit the heterogeneity. It takes the performance difference of peers into consideration to construct a dynamic variation of wrapped butterfly to achieve the goal. We also show how to optimize the performance of PPADHT in the view of hop counts by random graphs. Our simulation results show that the average lookup hop counts of the PPADHT is approximately a log scale with constant out degrees. And it can achieve loadbalance in two ways: both the document load and message routing load, without introducing any additional load on the peer. Here, the load balance means the load is proportion to the performance of peer.