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.
2826645
PROFILE COMPILER: Ontology-based, community-grounded, multilingual online services to support collaborative decision making
In todaypsilas industries, ontologies and the modern semantic technologies are offered as the potential solutions to support mutual understanding in the collaborative settings. Currently, organizations are unable to cope with collaborative decision making in a particular domain. Mastering domain knowledge and sharing decision rules is a complex yet important issue. In this paper, we first design a generic framework for community-grounded, collaborative decision making enabled, ontology based systems. This framework is constructed with three main engineering tracks: the linguistic engineering track, the ontology engineering track and the group decision engineering track. Each engineering track has its own methodology supported by a tool. Then, we use Semantic Decision Tables to elaborate the knowledge blocks resulting from these three engineering tracks. Semantic Decision Tables are mainly used (1) to elaborate concepts of the domain ontologies, (2) to gather semantically grounded decision rules within a decision group and (3) to provide tabular reports to the users. Finally, an online multilingual knowledge platform - the PROFILE COMPILER is developed as the result. It allows small or medium-sized enterprises (SMEs) to retrieve and personalize existing domain ontology, design and share their decision rules. We illustrate in the domain of Human Resource Management (HRM).
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.
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.
16610906
EIRS: An Intelligent E-Commerce Application System for Small Retailers in China
E-commerce is a fast growing channel for new business in China. However, Chinese small retailers have many difficulties in e-commerce applications nowadays, such as lack of IT skills, expensive of operation cost, etc. In this paper we present an intelligent retail system named eIRS which can help small retailers to implement their e-commerce strategies. eIRS whose single terminal entity looks like a telephone is an e-commerce platform linking product producers and retailers. It can reduce the redundant courses between product producers and retailers and also can act as an efficient medium, providing service similar to ICP for both of them. The test results of eIRS indicate that it creates a new win-win e-commerce model for producers and small retailers in China. We also analyze the Development Obstacles and Challenges of eIRS finally.
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.
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.
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.
14166643
3D Model Simplification Method Based on ROI
Based on edge-collapse algorithm and ROI (region of interest), an effective 3D mesh simplification method is proposed. During the simplification procedure, this method could successfully preserve a high resolution for the 3D part that the user is interested in while the rest parts could meet the basic requirement with lower resolution. The experiments support the conclusion.