Computer Networks and ISDN Systems
Automatic resource compilation by analyzing hyperlink structure and associated text
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Cited by (294)
Ranking influential and influenced stocks over time using transfer entropy networks
2023, Physica A: Statistical Mechanics and its ApplicationsTrust-aware location recommendation in location-based social networks: A graph-based approach
2023, Expert Systems with ApplicationsCitation Excerpt :Trustworthy users are obtained according to the trust scores, which are calculated as defined in Section 4.2. For experts and popular locations, HITS-based (Chakrabarti et al., 1998) algorithm is adopted, in which locations and users correspond to authority nodes and hub nodes of HITS algorithms, respectively. In order to calculate the location and user scores for expert and popular location estimation, our HITS-based algorithm iterates up to a predefined count on the LBSN graph.
CPR-TOPSIS: A novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy
2022, Physica A: Statistical Mechanics and its ApplicationsED-SWE: Event detection based on scoring and word embedding in online social networks for the internet of people
2021, Digital Communications and NetworksInfluential nodes selection to enhance data dissemination in mobile social networks: A survey
2020, Journal of Network and Computer ApplicationsVital nodes extracting method based on user's behavior in 5G mobile social networks
2019, Journal of Network and Computer ApplicationsCitation Excerpt :The third category schemes used eigenvector to evaluate users' significance in the network. Eigenvector centrality (Zhang et al., 2013b) and cumulative nomination (Chakrabarti et al., 1998) are grouped under this category. The last category schemes consider the importance of the user by removing it from the network (Chunlin and Zonghai, 2005).