The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems.Social Media platforms were initially developed for effective communication,but n...The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems.Social Media platforms were initially developed for effective communication,but now it is being used widely for extending and to obtain profit among business community.The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it.A giant network of people in social media is grouped together based on their similar properties to form a community.Commu-nity detection is recent topic among the research community due to the increase usage of online social network.Community is one of a significant property of a net-work that may have many communities which have similarity among them.Community detection technique play a vital role to discover similarities among the nodes and keep them strongly connected.Similar nodes in a network are grouped together in a single community.Communities can be merged together to avoid lot of groups if there exist more edges between them.Machine Learning algorithms use community detection to identify groups with common properties and thus for recommen-dation systems,health care assistance systems and many more.Considering the above,this paper presents alternative method SimEdge-CD(Similarity and Edge between's based Community Detection)for community detection.The two stages of SimEdge-CD initiallyfind the similarity among nodes and group them into one community.During the second stage,it identifies the exact affiliations of boundary nodes using edge betweenness to create well defined communities.Evaluation of proposed method on synthetic and real datasets proved to achieve a better accuracy-efficiency trade-of compared to other existing methods.Our proposed SimEdge-CD achieves ideal value of 1 which is higher than existing sim closure like LPA,Attractor,Leiden and walktrap techniques.展开更多
Ladys and gentlemen,good afternoon. As always, it’s a pleasure to be invited by the Vancouver Board of Trade to address the business community as well as many of my colleagues in the transportation sectors. I want to...Ladys and gentlemen,good afternoon. As always, it’s a pleasure to be invited by the Vancouver Board of Trade to address the business community as well as many of my colleagues in the transportation sectors. I want to tell you about an experience that has caused me to re-think the message I want to leave you with this afternoon. Rather than focusing on the Port of Vancouver today, and the things we do展开更多
Building a 15-minute radius livelihood service circle from the needs of residents is a topdown process of optimizing urban layout and promoting high-quality development implemented by the government.In September 2022,...Building a 15-minute radius livelihood service circle from the needs of residents is a topdown process of optimizing urban layout and promoting high-quality development implemented by the government.In September 2022,Xicheng District of Beijing served as a national pilot of the 15-minute radius livelihood service circle.Based on the data of POI,urban walking network and building outline,this paper studies the coverage of commercial service facilities in the 15-minute radius livelihood service circle of Chunshu Street by using kernel density analysis and urban network analysis tools.The research shows that the commercial facilities are concentrated in Zhuangsheng Square and Dazhalan commercial district.There are large gaps in housekeeping and couriers logistics facilities,which need to be further improved.展开更多
文摘The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems.Social Media platforms were initially developed for effective communication,but now it is being used widely for extending and to obtain profit among business community.The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it.A giant network of people in social media is grouped together based on their similar properties to form a community.Commu-nity detection is recent topic among the research community due to the increase usage of online social network.Community is one of a significant property of a net-work that may have many communities which have similarity among them.Community detection technique play a vital role to discover similarities among the nodes and keep them strongly connected.Similar nodes in a network are grouped together in a single community.Communities can be merged together to avoid lot of groups if there exist more edges between them.Machine Learning algorithms use community detection to identify groups with common properties and thus for recommen-dation systems,health care assistance systems and many more.Considering the above,this paper presents alternative method SimEdge-CD(Similarity and Edge between's based Community Detection)for community detection.The two stages of SimEdge-CD initiallyfind the similarity among nodes and group them into one community.During the second stage,it identifies the exact affiliations of boundary nodes using edge betweenness to create well defined communities.Evaluation of proposed method on synthetic and real datasets proved to achieve a better accuracy-efficiency trade-of compared to other existing methods.Our proposed SimEdge-CD achieves ideal value of 1 which is higher than existing sim closure like LPA,Attractor,Leiden and walktrap techniques.
文摘Ladys and gentlemen,good afternoon. As always, it’s a pleasure to be invited by the Vancouver Board of Trade to address the business community as well as many of my colleagues in the transportation sectors. I want to tell you about an experience that has caused me to re-think the message I want to leave you with this afternoon. Rather than focusing on the Port of Vancouver today, and the things we do
文摘Building a 15-minute radius livelihood service circle from the needs of residents is a topdown process of optimizing urban layout and promoting high-quality development implemented by the government.In September 2022,Xicheng District of Beijing served as a national pilot of the 15-minute radius livelihood service circle.Based on the data of POI,urban walking network and building outline,this paper studies the coverage of commercial service facilities in the 15-minute radius livelihood service circle of Chunshu Street by using kernel density analysis and urban network analysis tools.The research shows that the commercial facilities are concentrated in Zhuangsheng Square and Dazhalan commercial district.There are large gaps in housekeeping and couriers logistics facilities,which need to be further improved.
