基于PageRank和Node2vec的研究热点与集群发现——以国际深度学习研究领域为例

[目的/意义]为有效挖掘领域研究热点与集群,规避单纯基于频次统计的热点排序方法所存在的弊端,以及基于高频关键词共词网络集群发现方法所带来的偏差。[方法/过程]提出利用无向加权PagaRank算法进行研究热点排序,综合考量关键词之间共现的数量和质量,同时强调全部关键词共词网络的重要性,综合Node2vec表示学习和t-SNE聚类算法对全部关键词进行集群发现,以国际深度学习领域研究文献为例,分别进行热点排序和集群发现。[结果/结论]研究表明PageRank算法不仅能够区分频次统计算法无法区分的排名,而且从整体网络结构衡量研究热点,综合考量共现的数量和质量,使排序结果更为准确;整合Node2vec和t-SNE算法进行研究集群发现,可有效改善单纯利用高频关键词进行集群发现的不足,避免在有限的关联密切的高频关键词之间强制分门别类;综合热点和集群发现方法,可在凸显热点的基础上描述集群细节,有效揭示集群脉络。

Research on industrialization of eco-agriculture:theoretical framework and the case of Yunnan,China

The industrialization of eco-agriculture has applied modern science technology in accordance with ecological principles and has promoted agricultural production.As a subsystem of agricultural industrial clusters,the industrialization of eco-agriculture is the specific applications of cluster concept in the industrialization of eco-agriculture development.Industrialization of eco-agriculture cluster will achieve eco-agriculture and interact with industrial cluster which forms eco-agriculture integration and composite industry and ultimately realize the new benign circulation eco-agriculture model.According to the ecological engineering basic principles of recycling of the overall coordination,industrialization of eco-agriculture is focusing on the main systems operating coordination between the various subsystems and its various factors,and will maintain a reasonable ecological and economic structure to ensure the recycling of natural resources.Industrialization of eco-agriculture in Yunnan has adjusted the agricultural production structure to keep the stability of the gross grain production and economic development and has taken effective measures to vigorously improve land use and land productivity.Various ways of improving soil fertility has vigorously promoted other water-saving agricultural technologies.Ecological protection of rice no-tillage,cultivation of crop cultivation of the integrated control crop disease pests grass and agricultural production have taken the sustainable development.

Soft-Control for Collective Opinion of Weighted DeGroot Model

The DeGroot model is a classic model to study consensus of opinion in a group of individuals(agents). Consensus can be achieved under some circumstances. But when the group reach consensus with a convergent opinion value which is not what we expect, how can we intervene the system and change the convergent value? In this paper a mechanism named soft control is first introduced in opinion dynamics to guide the group's opinion when the population are given and evolution rules are not allowed to change. According to the idea of soft control, one or several special agents,called shills, are added and connected to one or several normal agents in the original group. Shills act and are treated as normal agents. The authors prove that the change of convergent opinion value is decided by the initial opinion and influential value of the shill, as well as how the shill connects to normal agents. An interesting and counterintuitive phenomenon is discovered: Adding a shill with an initial opinion value which is smaller(or larger) than the original convergent opinion value dose not necessarily decrease(or increase) the convergent opinion value under some conditions. These conditions are given through mathematical analysis and they are verified by the numerical tests. The authors also find out that the convergence speed of the system varies when a shill is connected to different normal agents. Our simulations show that it is positively related to the degree of the connected normal agent in scale-free networks.