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An Intelligent Topic Map-Based Approach to Detecting and Resolving Conflicts for Multi-Resource Knowledge Fusion

Article, was published by Feng Boqin and Lu Huimin at 2009-08-03

This paper proposes a novel concept of intelligent topic map, which embodies the multi-level of knowledge.

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In this study, we propose a novel concept of intelligent topic map, which embodies the multi-level, multi-granularity and inherent relevant characteristics of knowledge and realizes knowledge reasoning. With the intelligent topic map as infrastructure, we design a specific ontology fusion process for multi-resource knowledge fusion. Also, we define the taxonomy of merging conflicts which occur during the process of intelligent topic maps merging. We define and classify merging conflicts into data-level conflicts, structure-level conflicts, rule-level conflicts and temporary-level conflicts. We propose the detection and resolution schemes for each merging conflict. Additionally, we implement the multi-resource knowledge fusion conflicts detection and resolution system based on rules. The experimental results show that our method can correctly detect and resolve the conflicts in topic maps merging and it is helpful to improve the quality of multi-resource knowledge fusion.

Authors

Feng Boqin

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Lu Huimin

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Topic Maps is an excellent paradigm to support human thinking and to visualize networked information. As part of my PhD project, I therefore chose Topic Maps as the conceptual foundation for designing and implementing a software prototype for semantic knowledge retrieval.

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Topic Maps Lab auf der Cebit 2011
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