The presentation will mainly cover (1) What is HowNet? HowNet is an on-line common-sense knowledgebase unveiling inter-conceptual relationships and interattribute relationships of concepts as connoting in lexicons of the Chinese and their English equivalents. (2) How it functions in the computation of meaning and as a NLP platform? The presentation will show 9 HowNet-based application tools. All of them are not merely demonstration of some methodology or algorithm, but are real application tools that can be tested by users themselves. Apart from the tools that are specially designed to deal with Chinese, most of the tools are bilingual, even the WSD tool.
Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What’s more, VoteRank has superior computational efficiency.
The presentation will mainly cover (1) What is HowNet? HowNet is an on-line common-sense knowledgebase unveiling inter-conceptual relationships and interattribute relationships of concepts as connoting in lexicons of the Chinese and their English equivalents. (2) How it functions in the computation of meaning and as a NLP platform? The presentation will show 9 HowNet-based application tools. All of them are not merely demonstration of some methodology or algorithm, but are real application tools that can be tested by users themselves. Apart from the tools that are specially designed to deal with Chinese, most of the tools are bilingual, even the WSD tool.
Currently, supply chain networks can span the whole world, and any disruption of these networks may cause economic losses, decreases in sales and unsustainable supplies. Resilience, the ability of the system to withstand disruption and return to a normal state quickly, has become a new challenge during the supply chain network design. This paper defines a new resilience measure as the ratio of the integral of the normalized system performance within its maximum allowable recovery time after the disruption to the integral of the performance in the normal state. Using the maximum allowable recovery time of the system as the time interval under consideration, this measure allows the resilience of different systems to be compared on the same relative scale, and be used under both scenarios that the system can or cannot restore in the given time. Two specific resilience measures, the resilience based on the amount of product delivered and the resilience based on the average delivery distance, are provided for supply chain networks. To estimate the resilience of a given supply chain network, a resilience simulation method is proposed based on the Monte Carlo method. A four-layered hierarchial mobile phone supply chain network is used to illustrate the resilience quantification process and show how network structure affects the resilience of supply chain networks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.