• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.5 no.3
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• pp.27-45
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• 2010

It is strongly believed that multicast will become one of the most promising services on internet for the next generation. Multicast service can be deployed either on network-layer or application-layer. IP multicast (network-layer multicast) is implemented by network nodes (i.e., routers) and avoids multiple copies of the same datagram on the same link. Despite the conceptual simplicity of IP multicast and its obvious benefits, it has not been widely deployed since there remain many unresolved issues. As an alternative to IP multicast, overlay multicast (application-layer multicast) implements the multicast functionality at end hosts rather than routers. This may require more overall bandwidth than IP multicast because duplicate packets travel the same physical links multiple times, but it provides an inexpensive, deployable method of providing point-to-multipoint group communication. In this paper we develop an efficient method applied greedy algorithm for solving two models of overlay multicast routing protocol that is aimed to construct MDST (Minimum Diameter Spanning Tree : minimum cost path from a source node to all its receivers) and MST (Minimum Spanning Tree : minimum total cost spanning all the members). We also simulate and analyze MDST and MST.

• Journal of KIISE
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• v.42 no.12
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• pp.1522-1534
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• 2015

This work presents a new method that can predict, without the use of training data, whether an input essay is written on a given topic. ConceptNet is a common-sense knowledge base that is generated automatically from sentences that are extracted from a variety of document types. An essay prompt is the topic that an essay should be written about. The method that is proposed in this paper uses ConceptNet and an essay prompt to decide whether or not an input essay is off-topic. We introduce a way to find the shortest path between two nodes on ConceptNet, as well as a way to calculate the semantic similarity between two nodes. Not only an essay prompt but also a student's essay can be represented by concept nodes in ConceptNet. The semantic similarity between the concepts that represent an essay prompt and the other concepts that represent a student's essay can be used for a calculation to rank "on-topicness" ; if a low ranking is derived, an essay is regarded as off-topic. We used eight different essay prompts and a student-essay collection for the performance evaluation, whereby our proposed method shows a performance that is better than those of the previous studies. As ConceptNet enables the conduction of a simple text inference, our new method looks very promising with respect to the design of an essay prompt for which a simple inference is required.

• 한국벤처창업학회:학술대회논문집
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• 2010.08a
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• pp.71-89
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• 2010

It is strongly believed that multicast will become one of the most promising services on internet for the next generation. Multicast service can be deployed either on network-layer or application-layer. IP multicast (network-layer multicast) is implemented by network nodes (i.e., routers) and avoids multiple copies of the same datagram on the same link. Despite the conceptual simplicity of IP multicast and its obvious benefits, it has not been widely deployed since there remain many unresolved issues. As an alternative to IP multicast, overlay multicast (application-layer multicast) implements the multicast functionality at end hosts rather than routers. This may require more overall bandwidth than IP multicast because duplicate packets travel the same physical links multiple times, but it provides an inexpensive, deployable method of providing point-to-multipoint group communication. In this paper we develop an efficient method applied greedy algorithm for solving two models of overlay multicast tree building problem that is aimed to construct MDST (Minimum Diameter Spanning Tree : minimum cost path from a source node to all its receivers) and MST (Minimum Spanning Tree : minimum total cost spanning all the members). We also simulate and analyze MDST and MST.