Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Ricky Laishram"'
Autor:
Ricky Laishram, Sucheta Soundarajan
Publikováno v:
2022 IEEE International Conference on Data Mining (ICDM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff06b173a597db85b7bf07cd35ed3c50
https://doi.org/10.1109/icdm54844.2022.00124
https://doi.org/10.1109/icdm54844.2022.00124
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 16:1-32
In this article, we consider the problem of crawling a multiplex network to identify the community structure of a layer-of-interest. A multiplex network is one where there are multiple types of relationships between the nodes. In many multiplex netwo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e13c8fc3a942ddd8e8689c2833b422c4
https://doi.org/10.1145/3451527
https://doi.org/10.1145/3451527
Publikováno v:
AAAI
We examine the problem of crawling the community structure of a multiplex network containing multiple layers of edge relationships. While there has been a great deal of work examining community structure in general, and some work on the problem of sa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2fdc87018f54f2643dee459b378a7d4
https://doi.org/10.1609/aaai.v33i01.3301168
https://doi.org/10.1609/aaai.v33i01.3301168
Publikováno v:
WebSci
In many network applications, it may be desirable to conceal certain target nodes from detection by a data collector, who is using a crawling algorithm to explore a network. For example, in a computer network, the network administrator may wish to pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1424164067a7710c56963a8ed397c06c
https://doi.org/10.1145/3447535.3462500
https://doi.org/10.1145/3447535.3462500
Publikováno v:
WebSci
Over the past two decades, online social networks have attracted a great deal of attention from researchers. However, before one can gain insight into the properties or structure of a network, one must first collect appropriate data. Data collection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca284d9306500b2353e7c71a545b0afa
https://doi.org/10.1145/3201064.3201066
https://doi.org/10.1145/3201064.3201066
Publikováno v:
WWW
The concept of k-cores is important for understanding the global structure of networks, as well as for identifying central or important nodes within a network. It is often valuable to understand the resilience of the k-cores of a network to attacks a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffd131357b1d44c09f36b824e78fa51b
https://doi.org/10.1145/3178876.3186127
https://doi.org/10.1145/3178876.3186127
Publikováno v:
IEEE BigData
INFOCOM Workshops
INFOCOM Workshops
When studying large-scale networks, including the Web and computer networks, it is first necessary to collect appropriate data. There is a large body of literature on web crawling and network sampling in general; however, this work typically assumes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f570f10d3f78cd53acdd9969d3336ad2
https://doi.org/10.1109/bigdata.2016.7841092
https://doi.org/10.1109/bigdata.2016.7841092
Publikováno v:
IEEE BigData
In this work, we propose Max-Node sampling, a novel sampling algorithm for data collection. The goal of Max-Node is to maximize the number of nodes observed in the sample, given a budget constraint. Max-Node is based on the intuition that networks co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed75392ec4aa06281c2cea1efcb2a1d5
https://doi.org/10.1109/bigdata.2016.7841070
https://doi.org/10.1109/bigdata.2016.7841070
Publikováno v:
ICTAI
In social networks that change with time, an important problem is the prediction of new links that may be formed in the future. Existing works on link prediction have focused only on networks where links are permanent, an assumption that is not valid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d978cd3f4f03d5d7609d39660cbc3cfc
https://doi.org/10.1109/ictai.2016.0098
https://doi.org/10.1109/ictai.2016.0098