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The integration of Traditional Chinese Medicine (TCM) and Western Medicine (WM) requires extensive interdisciplinary and cross-cultural collaboration. The productivity of integrated studies is often limited by the lack of understanding between practitioners from different cultural backgrounds. Information technologies, especially the Semantic Web and ontologies, can facilitate the exchange of medical...
The World Wide Web connects a wide variety of communities in medical domain, and provides a platform for knowledge exchange and integration between Traditional Chinese Medicine (TCM) and biomedicine. However, the cultural gaps between TCM and Western Medicine hinder cross-cultural communication. We utilize Semantic Web technologies to build a knowledge base that integrates distributed and heterogeneous...
Complex networks of direct relevance to biomedicine have not yet been fully mapped largely due to the incompleteness, isolation, and heterogeneity of data. The Semantic Web, by providing a technical framework for the integration and sharing of heterogeneous databases in different domains, can potentially enable more effective complex network mapping and analysis. However, the feasibility of using...
Linked data is a decentralized space of interlinked Resource Description Framework (RDF) graphs that are published, accessed, and manipulated by a multitude of Web agents. Here, we present a multi-agent framework for mining hypothetical semantic relations from linked data, in which the discovery, management, and validation of relations can be carried out independently by different agents. These agents...
As a part of the Semantic Web, Linked data is used to connect and share related data on the Web. Compared with traditional Web documents, it has following advantages: more structural; easily understood by humans; describing the things rather than documents or pages; stronger associations. For these reasons, it is more suitable for information search and data mining. In this paper, we proposed a novel...
Linked Data is an open data space that emerges from the publication and interlinking of structured data on the Web using the Semantic Web technologies. How to utilize this wealth of data is currently a focused research theme of the Semantic Web community. In this paper, we aim to utilize Linked Data to generate semantic annotations for frequent patterns extracted from textual documents. First, we...
The efforts of publishing and interlinking structured data on the Semantic Web will result in a global network of databases, or the Linked Data, which provides huge potential for discovering hidden relationships. We present a multi-agent framework for Semantic Associations Discovery (SAD) from distributed linked data on the Semantic Web. Here, agents collaborate in SAD by publishing inter-dependent...
As increasing linked datasets are progressively published on the semantic Web, discovering the most similar entities in large linked datasets becomes crucial in many semantic applications. Conventional approaches usually draw upon either ontology taxonomy or relationships unilaterally. In this paper, we present a novel approach which utilizes node and link types together with the topology of semantic...
Nowadays, social networks play an important role in our lives, in which information and knowledge are exchanged, shared and transformed. With time, large volumes of real-world data have been accumulated capturing diversified application domains. However, heterogeneity and incompleteness of data make social networks perform as 'data isolated islands' separated to each other. In this paper, we propose...
The proliferation of online social websites results in the accumulation of a large volume of real-world data capturing social networks in diversified application domains. However, social networks are always separated with each other that causes the data isolated island phenomenon, which becomes impedance to implementing complex data analysis that requires comprehensive data stored in several social...
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