Fault-tolerant Semantic Mappings Among Heterogeneous and Distributed Local Ontologies

ABSTRACT Overcoming semantic mapping faults, i.e. semantic incompatibility, is a vital issue for the success of semantic-based peer-to-peer systems. There are various research efforts which address the classification and the resolution of the semantic mapping fault problem, i.e. translation errors. All of the precedent research related to semantic mapping faults demonstrates one significant shortcoming. This flaw is the inability to discriminate between non-permanent and permanent semantic mapping faults, i.e. how long do semantic incompatibilities stay effective and are the semantic incompatibilities permanent or temporary? The current research examines the destructive effect of semantic mapping faults on the Emerging Semantics, i.e. bottom-up construction of ontology and proposes a solution to detect temporal semantic mapping faults. The current research also demonstrates that fault-tolerant semantic mapping will result in Emerging Semantics which are more complete and agreeable than those domain ontologies that are built without consideration for fault-tolerant semantic mapping

Gender Prediction of Journalists from Writing Style

Web-based Kurdish media have seen a tangible growth in the last few years. There are many factors that have contributed into this rapid growth. These include an easy access to the internet connection, the low price of electronic gadgets and pervasive usage of social networking. The swift development of the Kurdish web-based media imposes new challenges that need to be addressed. For example, a newspaper article published online possesses properties such as author name, gender, age, and nationality among others. Determining one or more of these properties, when ambiguity arises, using computers is an important open research area. In this study the journalist’s gender in web-based Kurdish media determined using computational linguistic and text mining techniques. 75 web-based Kurdish articles used to train artificial model designed to determine the gender of journalists in web-based Kurdish media. Articles were downloaded from four different well known web-based Kurdish newspapers. 61 features were extracted from each article; these features are distinct in discriminating between genders. The Multi-Layer Perceptron (MLP) artificial neural network is used as a classification technique and the accuracy received were 76%

From P2P to reliable semantic P2P systems

Current research to harness the power of P2P networks involves building reliable Semantic Peer-to-Peer (SP2P) systems. SP2P systems combine two complementary technologies: P2P networking and ontologies. There are several types of SP2P systems with applications to knowledge management systems, databases, the Semantic Web, emergent semantics, web services, and information systems. Correct semantic mapping is fundamental for success of SP2P systems where semantic mapping refers to semantic relationship between concepts from different ontologies. Current research on SP2P systems has emphasized semantics at the cost of dealing with the traditional issues of P2P networks of reliability and scalability. As a result of their lack of resilience to temporary mapping faults, SP2P systems can suffer from disconnection failures. Disconnection failures arise when SP2P systems that use adaptive query routing methods treat temporary mapping faults as permanent mapping faults. This paper identifies the disconnection failure problem due to temporary semantic mapping faults and proposes an algorithm to resolve it. To identify the problem, we will use a simulation model of SP2P systems. The Fault-Tolerant Adaptive Query Routing (FTAQR) algorithm proposed to resolve the problem is an adaptation of the generous tit-for-tat method originally developed in evolutionary game theory. The paper demonstrates that the reliability of an SP2P system increases by using the algorithm