5091874
Integrating Web Services into Ontology-Based Web Portal
With the explosive emerged Web services, the Web becomes a world of information and applications. So portals whose goal is presenting a structured view onto the Web should provide users with a single point access to multiple types of not only information but also services. Recently, many systems have been developed using ontology-driven approaches to automatically generate and manage Web portals. However, all of them lack the integration of Web services. In this paper, we describe SPortS, an OWL-DL(Web Ontology Language-Description Logics) based portal generation system that integrates semantic Web services into generated portals at the presentation level, the data level and the function level. We present the portal generation process, the query decomposition and the service recommendation algorithms through which semantic Web services are integrated tightly into the generated portal.
150914
An enhanced model for searching in semantic portals
Semantic Portal is the next generation of web portals that are powered by Semantic Web technologies for improved information sharing and exchange for a community of users. Current methods of searching in Semantic Portals are limited to keyword-based search using information retrieval (IR) techniques, ontology-based formal query and reasoning, or a simple combination of the two. In this paper, we propose an enhanced model that tightly integrates IR with formal query and reasoning to fully utilize both textual and semantic information for searching in Semantic Portals. The model extends the search capabilities of existing methods and can answer more complex search requests. The ideas in a fuzzy description logic (DL) IR model and a formal DL query method are employed and combined in our model. Based on the model, a semantic search service is implemented and evaluated. The evaluation shows very large improvements over existing methods.
16851151
UMR: a multi-round algorithm for scheduling divisible workloads
In this paper we present an algorithm for scheduling parallel divisible workload applications. Our algorithm uses multiple rounds to overlap communication and computation between a master and several workers. We use "uniform" rounds, i.e. a fixed amount of work is sent out to all workers at each round. This restriction makes it possible to compute an approximately optimal number of rounds, which was not possible for previously proposed algorithms. In addition, we use more realistic platform models than those used in previous works. We provide an analysis of our algorithm both for homogeneous and heterogeneous platforms and present simulation results.
7655844
Music emotion classification: a fuzzy approach
Due to the subjective nature of human perception, classification of the emotion of music is a challenging problem. Simply assigning an emotion class to a song segment in a deterministic way does not work well because not all people share the same feeling for a song. In this paper, we consider a different approach to music emotion classification. For each music segment, the approach determines how likely the song segment belongs to an emotion class. Two fuzzy classifiers are adopted to provide the measurement of the emotion strength. The measurement is also found useful for tracking the variation of music emotions in a song. Results are shown to illustrate the effectiveness of the approach.
5978696
From BPEL4WS to OWL-S: integrating e-business process descriptions
With the rapid deployment of e-services, many workflow-like e-business process definition languages come into existence. At the same time, ontology Web language for services (OWL-S) aims to build an ontology language to support the integration of various specifications. There has been some work on mapping WSDL (Web services description language) to OWL-S to build a connection between the Web service and service profile. However, in the sense of activity relationships, there has been no effort so far trying to build the OWL-S service model from a workflow process model. Therefore, we design and develop an innovative mapping tool to translate BPEL4WS (business process execution language for Web services) to OWL-S. Through this mapping, semantics in the traditional business process specifications can be enriched significantly to enable more flexible and automatic e-service functions by using existing OWL-S tools such as composition and discovery, especially the execution of workflow-based services.
43250103
An Agent-Based Ontological Approach for Information Reorganisation
This paper presents a novel approach for information reorganisation which is particularly suitable for distributed computing, such as Web services. An agent-based architecture is developed to cope with service agents' on and off and provide semantic support for implementation of complex e-business applications that may span diverse enterprises. A frame-based ontology representation is discussed. The representation is well suited for representing complex relationships that are unavailable in current ontology related work. Our approach aims to support dynamic information reorganisation in the Internet based e-business applications. The obtained information can serve for the knowledge acquisition purpose.
15796925
Combining Multiple Learning Strategies for Effective Cross Validation
Parameter tuning through cross-validation becomes very diicult when the validation set contains no or only a few examples of the classes in the evaluation set. We address this open challenge by using a combination of classiiers with diierent performance characteristics to eeectively reduce the performance variance on average of the overall system across all classes, including those not seen before. This approach allows us to tune the combination system on available but less-representative validation data and obtain smaller performance degradation of this system on the evaluation data than using a single-method classiier alone. We tested this approach by applying k-Nearest Neighbor, Rocchio and Language Modeling classiiers and their combination to the event tracking problem in the Topic Detection and Tracking (TDT) domain, where new classes (events) are created constantly over time, and representative validation sets for new classes are often diicult to obtain on time. When parameters tuned on an early benchmark TDT corpus were evaluated on a later TDT benchmark corpus with no overlapping events, we observed a 38-65% reduction in tracking cost (a weighted combination of errors) by the combined system over the individual methods evaluated under the same conditions, strongly suggesting the robustness of this approach as a solution for improving cross-class performance consistency of statistical classi-ers when standard cross-validation fails due to the lack of representative validation sets.