16344510
On Constructing, Grouping and Using Topical Ontology for Semantic Matching
An ontology topic is used to group concepts from different contexts (or even from different domain ontologies). This paper presents a pattern-driven modeling methodology for constructing and grouping topics in an ontology (PAD-ON methodology), which is used for matching similarities between competences in the human resource management (HRM) domain. The methodology is supported by a tool called PAD-ON. This paper demonstrates our recent achievement in the work from the EC Prolix project. The paper approach is applied to the training processes at British Telecom as the test bed.
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.
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.
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.
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.
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.
29100810
An Expert System Based Approach to Modeling and Selecting Requirement Engineering Techniques
The importance of requirements engineering (RE) has been raised numerous times in literatures. To choose suitable RE techniques for a particular project in a given situation is a challenging task, requiring substantial expertise and efforts. To help solving this problem, an expert system based approach is proposed. This expert system uses the knowledge from domain experts to model the causal factors of RE techniques. It can select suitable RE techniques for a software project. A web-based questionnaire is created in the first place to collect the expertise available in the community. The information collected by the questionnaire is analyzed and transformed into a new dataset for constructing a Bayesian Belief Network (BBN). The resulting BBN integrated with a GUI forms an expert system for RE techniques modeling and selection. Empirical study validates the transformed dataset and shows that the expert system outperforms other predictors in selecting suitable RE techniques in different RE phases.
14763261
Zero-Efficient Buffer Design for Reliable Network-on-Chip in Tiled Chip-Multi-Processor
Network-on-chip (NoC) is a promising solution for efficient interconnection between processor cores in chip-multi-processor (CMP). This paper is focusing on the energy-efficient design of buffers, a group of the most important components in NoC. From our investigation, an overwhelming majority of "zero" is contained in the packets transmitting in NoC for CMP. A zero-efficient buffer design is proposed as well as the error control scheme. Compared with conventional design, up to 43% energy consumption can be saved. We use a 90 nm CMOS process in our simulation.
38545491
Defining Re-usable Composite Aspect Patterns: An FDAF Based Approach
Architecting secure systems is an important and challenging problem. Solutions to model individual, or atomic, security capabilities have been proposed, including security patterns, component based, aspect-oriented, and service-oriented approaches. However, little work is available on how to model reusable compositions of security capabilities, where the security capabilities interact with each other and other parts of the system design. Here, an aspect-oriented approach to modeling composite aspects is presented. The approach is defined as an extension to the Formal Design Analysis Framework (FDAF). The FDAF metamodel is extended to support the static representation of composite aspects and an approach to defining the compositions is introduced. A composite aspect that provides Account Lockout with Selective Event Logging (ALSEL) capabilities is used as an example.
15542014
Efficient checkpointing of java software using context-sensitive capture and replay
Checkpointing and replaying is an attractive technique that has been used widely at the operating/runtime system level to provide fault tolerance. Applying such a technique at the application level can benefit a range of software engineering tasks such as testing of long-running programs, automated debugging, and dynamic slicing. We propose a checkpointing/replaying technique for Java that operates purely at the language level, without the need for JVM-level or OS-level support. At the core of our approach are static analyses that select, at certain program points, a safe subset of the program state to capture and replay. Irrelevant statements before the checkpoint are eliminated using control-dependence-based slicing; the remaining statements together with the captured run-time values are used to indirectly recreate the call stack of the original program at the checkpoint. At the checkpoint itself and at certain subsequent program points, the replaying version restores parts of the program state that are necessary for execution of the surrounding method. Our experimental studies indicate that the proposed static and dynamic analyses have the potential to reduce significantly the execution time for replaying, with low run-time overhead for checkpointing.