Ontology-based knowledge management systems enable the automatic discovery, sharing and reuse of structured data sources on the semantic web. With the emergence of multilingual ontologies, accessing knowledge across n...
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Ontology-based knowledge management systems enable the automatic discovery, sharing and reuse of structured data sources on the semantic web. With the emergence of multilingual ontologies, accessing knowledge across natural language barriers has become a pressing issue for the multilingual semantic web. In this paper, a semantic-oriented cross-lingual ontology mapping (SOCOM) framework is proposed to enhance interoperability of ontology-based systems that involve multilingual knowledge repositories. The contribution of cross-lingual ontology mapping is demonstrated in two use case scenarios. In addition, the notion of appropriate ontology label translation, as employed by the SOCOM framework, is examined in a cross-lingual ontology mapping experiment involving ontologies with a similar domain of interest but labelled in English and Chinese respectively. Preliminary evaluation results indicate the promise of the crosslingual mapping approach used in the SOCOM framework, and suggest that the integrated appropriate ontology label translation mechanism is effective in the facilitation of monolingual matching techniques in cross-lingual ontology mapping scenarios. Copyright is held by the author/owner(s).
Similarity plays an important role in many multimedia retrieval applications. However, it often has many facets and its perception is highly subjective - very much depending on a person's background or retrieval g...
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In the last years several drafts, recommendations and concepts for a graphical notation for Topic Maps have been published, but till today no graphical notation is generally approved and used in the Topic Maps communi...
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ISBN:
(纸本)9783941152052
In the last years several drafts, recommendations and concepts for a graphical notation for Topic Maps have been published, but till today no graphical notation is generally approved and used in the Topic Maps community. In this paper we present GTMalpha as a conceptual new notation for a graphical representation of Topic Maps. Our objective is, to provide a practical usable notation, which allows a complete, consistent as well as easy to use graphical representation of any given topic map draft. GTMalpha provides a domain as well as a subject centric view and most important it considers the unique characteristics of the Topic Maps paradigm. This paper serves as a user oriented GTMalpha manual for ontology designers, domain experts as well as users.
Quality measures are important to evaluate graph clustering algorithms by providing a means to assess the quality of a derived cluster structure. In this paper, we focus on overlapping graph structures, as many real-w...
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ISBN:
(纸本)9789898425980
Quality measures are important to evaluate graph clustering algorithms by providing a means to assess the quality of a derived cluster structure. In this paper, we focus on overlapping graph structures, as many real-world networks have a structure of highly overlapping cohesive groups. We propose three methods to adapt existing crisp quality measures such that they can handle graph overlaps correctly, but also ensure that their properties for the evaluation of crisp graph clusterings are preserved when assessing a crisp cluster structure. We demonstrate our methods on such measures as Density, Newman's modularity and Conductance. We also propose an enhancement of an existing modularity measure for networks with overlapping structure. The newly proposed measures are analysed using experiments on artificial graphs that possess overlapping structure. For this evaluation, we apply a graph generation model that creates clustered graphs with overlaps that are similar to real-world networks i.e. their node degree and cluster size distribution follow a power law.
Federated policy systems are required to support the emergent complexity and organizational heterogeneity of modern Internet service delivery. This paper presents a distributed policy management approach which utilize...
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Service discovery protocols are extremely important for developing distributed applications in ad-hoc environments. However to perform Service Discovery in mobile ad-hoc networks requires the design and development of...
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Both Content analysis and link, analysis have its advantages in measuring relationships among documents. In this paper. we propose a new method to combine these two methods to compute the similarity of research papers...
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ISBN:
(纸本)9783540881919
Both Content analysis and link, analysis have its advantages in measuring relationships among documents. In this paper. we propose a new method to combine these two methods to compute the similarity of research papers so that we can do clustering of these papers more accurately. In order to improve the efficiency of similarity calculation, we develop a strategy to deal with the relationship graph separately, without affecting the accuracy. We also design an approach to assign different weights to different links to the papers, which can enhance the accuracy of similarity calculation. The experimental results conducted oil ACM data Set show that our new algorithm. S-SimRank, outperforms other algorithms.
The heterogeneity of learner models in structure, syntax and semantics makes sharing them a significant challenge for existing educational web systems. Creating mappings between the different types of learner models i...
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ISBN:
(纸本)9789898425515
The heterogeneity of learner models in structure, syntax and semantics makes sharing them a significant challenge for existing educational web systems. Creating mappings between the different types of learner models is one technique that is used when attempting to overcome these issues. This paper presents an overview of research currently being conducted in the area of learner model exchange and defines a categorization, derived from existing educational web systems, of the different mapping types that are required for learner model mapping. Following this, a framework is presented that supports the creation and validation of these different mapping types and the exchange of learner information between multiple heterogeneous educational web systems.
By analyzing data gathered through Online Learning(OL)systems,data mining can be used to unearth hidden relationships between topics and trends in student ***,in this paper,we show how data mining techniques such as c...
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By analyzing data gathered through Online Learning(OL)systems,data mining can be used to unearth hidden relationships between topics and trends in student ***,in this paper,we show how data mining techniques such as clustering and association rule algorithms can be used on historical data to develop a unique recommendation system *** our implementation,we utilize historical data to generate association rules specifically for student test marks below a threshold of 60%.By focusing on marks below this threshold,we aim to identify and establish associations based on the patterns of weakness observed in the past ***,we leverage K-means clustering to provide instructors with visual representations of the generated *** strategy aids instructors in better comprehending the information and associations produced by the *** clustering helps visualize and organize the data in a way that makes it easier for instructors to analyze and gain insights,enabling them to support the verification of the relationship between *** can be a useful tool to deliver better feedback to students as well as provide better insights to instructors when developing their *** paper further shows a prototype implementation of the above-mentioned concepts to gain opinions and insights about the usability and viability of the proposed system.
This paper presents two real-world case studies focussing on descriptive data mining for decision-makers. For that, we first propose a process-oriented design of descriptive data mining that helps in describing and pe...
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This paper presents two real-world case studies focussing on descriptive data mining for decision-makers. For that, we first propose a process-oriented design of descriptive data mining that helps in describing and performing such projects. Finally, we discuss important lessons learned during the implementation of the respective projects.
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