A common approach to mitigate the effects of ontology heterogeneity is to discover and express the specific correspondences between different ontologies. An open research question is: how should such ontology mappings...
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ISBN:
(纸本)1902956850
A common approach to mitigate the effects of ontology heterogeneity is to discover and express the specific correspondences between different ontologies. An open research question is: how should such ontology mappings be represented. In recent years several proposals for an ontology mapping representation have been published, but till today no format is officially standardized or generally accepted in the community. In this paper we will present a new evaluation framework for ontology mapping representations for a pragmatic state of the art overview of their characteristics. In particular we are interested how current ontology mapping representations can support the management of ontology mappings (sharing, re-use, alteration) as well as how suitable they are for different mapping tasks.
A key problem in supporting multilingual information retrieval and digital content management is reasoning about overlapping context domains. Ontologies are currently emerging as representation techniques for overlapp...
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ISBN:
(纸本)1902956850
A key problem in supporting multilingual information retrieval and digital content management is reasoning about overlapping context domains. Ontologies are currently emerging as representation techniques for overlapping complimentary context domains. To date, research has focused on the mappings of monolingual ontologies, however, the issue of mapping ontologies written in different natural languages is relatively unexplored at the moment. This paper discusses challenges in the area of multilingual ontology mapping and proposes the semantic oriented mapping for multilingual ontologies (SOMMO) framework to advance the state of the art in multilingual ontology mapping. The SOMMO framework aims to improve multilingual ontology mapping results generated from existing monolingual ontology matching techniques by evaluating the semantics embedded in both the source and target ontologies.
Domain analysis in software product line （SPL） development provides a basis for core assets design and imple- mentation by a systematic and comprehensive commonality/variability analysis. In feature-oriented SPL met...
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Domain analysis in software product line （SPL） development provides a basis for core assets design and imple- mentation by a systematic and comprehensive commonality/variability analysis. In feature-oriented SPL methods, products of the domain analysis are domain feature models and corresponding feature decision models to facilitate application-oriented customization. As in requirement analysis for a single system, the domain analysis in the SPL development should con- sider both flmctional and nonfunctional domain requirements. However, the nonfunctional requirements （NFRs） are often neglected in the existing domain analysis methods. In this paper, we propose a context-based method of the NFR analysis for the SPL development. In the method, NFRs are materialized by connecting nonfunctional goals with real-world context, thus NFR elicitation and variability analysis can be performed by context analysis for the whole domain with the assistance of NFR templates and NFR graphs. After the variability analysis, our method integrates both functional and nonfunc- tional perspectives by incorporating the nonfunctional goals and operationalizations into an initial functional feature model. NFR-related constraints are also elicited and integrated. Finally, a decision model with both functional and nonfunctional perspectives is constructed to facilitate application-oriented feature model customization. A computer-aided grading system （CAGS） product line is employed to demonstrate the method throughout the paper.
Ubiquitous computing (ubicomp), as envisaged by Weiser [22], is heavily user-centric and largely concerned with applications specifically designed to meet end-user needs. Sensor populated ubicomp environments differen...
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ISBN:
(纸本)9789639799455
Ubiquitous computing (ubicomp), as envisaged by Weiser [22], is heavily user-centric and largely concerned with applications specifically designed to meet end-user needs. Sensor populated ubicomp environments differentiate these applications from existing mobile and distributed systems through context awareness. For the system developer, the problems of heterogeneity and scalability are felt most keenly when designing this adaptive behaviour. A context-aware ubicomp system needs to operate reliably over the wide variety of situations that may be encountered. In this paper we present a technical architecture which has been implemented to support scalable, cost-effective, runtime experimentation using a framework of models to support informed decision making in an iterative design cycle.
A common approach to mitigate the effects of ontology heterogeneity is to discover and express the specific correspondences (mappings) between different ontologies. An open research question is: how should such ontolo...
详细信息
ISBN:
(纸本)1891706241
A common approach to mitigate the effects of ontology heterogeneity is to discover and express the specific correspondences (mappings) between different ontologies. An open research question is: how should such ontology mappings be represented? In recent years several proposals for an ontology mapping representation have been published, but as yet no format is officially standardised or generally accepted in the community. In this paper we will present the results of a systematic analysis of ontology mapping representations to provide a pragmatic state of the art overview of their characteristics. In particular we are interested how current ontology mapping representations can support the management of ontology mappings (sharing, re-use, alteration) as well as how suitable they are for different mapping tasks.
Social bookmarking tools become more and more popular nowadays and tagging is used to organize information and allow users to recall or search the resources. Users need to type the tags whenever they post a resource, ...
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Social bookmarking tools become more and more popular nowadays and tagging is used to organize information and allow users to recall or search the resources. Users need to type the tags whenever they post a resource, so that a good tag recommendation system can ease the process of finding some useful and relevant keywords for users. Researchers have made lots of relevant work for recommendation system, but those traditional collaborative systems do not fit to our tag recommendation. In this paper, we present two different methods: a simple language model and an adaption of topic model. We evaluate and compare these two approaches and show that a combination of these two methods will perform better results for the task one of PKDD Challenge 2009.
With the rapid development of web2.0 technologies, tagging become much more important today to organize information and help users search the information they need with social bookmarking tools. In order to finish the...
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With the rapid development of web2.0 technologies, tagging become much more important today to organize information and help users search the information they need with social bookmarking tools. In order to finish the second task of ECML PKDD challenge 2009, we propose a graph-based collaborative filtering tag recommendation system. We also refer to an algorithm called FolkRank, which is an adaptation of the famous Page Rank. We evaluate and compare these two approaches and show that a combination of these two methods will perform better results for our task.
This paper presents an undertaken research work about the development of an Adaptive Tourism Modeling System which attempts to correctly model a tourism web application user profile. This paper will follow the methodo...
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Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in ...
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ISBN:
(纸本)9781424452422
Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in characterizing the object similarities in networks, such as the Web, by exploiting the object-to-object relationship. Unfortunately, it is prohibitively expensive to compute the link-based similarity in a relatively large graph. In this paper, based on the observation that link-based similarity scores of real world graphs follow the power-law distribution, we propose a new approximate algorithm, namely Power-SimRank, with guaranteed error bound to efficiently compute link-based similarity measure. We also prove the convergence of the proposed algorithm. Extensive experiments conducted on real world datasets and synthetic datasets show that the proposed algorithm outperforms SimRank by four-five times in terms of efficiency while the error generated by the approximation is small.
Modern smart buildings utilize sensor networks for facilities management applications such as energy monitoring. However as buildings become progressively more embedded with sensor networks, the challenge of managing ...
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