Zobrazeno 1 - 10
of 47
pro vyhledávání: '"van der Loo, Mark P. J."'
In this paper we introduce a general version of the anonymization problem in social networks, in which the goal is to maximize the number of anonymous nodes by altering a given graph. We define three variants of this optimization problem, being full,
Externí odkaz:
http://arxiv.org/abs/2409.16163
Privacy-aware sharing of network data is a difficult task due to the interconnectedness of individuals in networks. An important part of this problem is the inherently difficult question of how in a particular situation the privacy of an individual n
Externí odkaz:
http://arxiv.org/abs/2407.02290
Autor:
van der Loo, Mark P. J.
Partitioning a data set by one or more of its attributes and computing an aggregate for each part is one of the most common operations in data analyses. There are use cases where the partitioning is determined dynamically by collapsing smaller subset
Externí odkaz:
http://arxiv.org/abs/2406.09887
Ensuring privacy of individuals is of paramount importance to social network analysis research. Previous work assessed anonymity in a network based on the non-uniqueness of a node's ego network. In this work, we show that this approach does not adequ
Externí odkaz:
http://arxiv.org/abs/2306.13508
Data validation is the activity where one decides whether or not a particular data set is fit for a given purpose. Formalizing the requirements that drive this decision process allows for unambiguous communication of the requirements, automation of t
Externí odkaz:
http://arxiv.org/abs/2012.12028
Autor:
van der Loo, Mark P. J.
Monitoring data while it is processed and transformed can yield detailed insight into the dynamics of a (running) production system. The lumberjack package is a lightweight package allowing users to follow how an R object is transformed as it is mani
Externí odkaz:
http://arxiv.org/abs/2005.04050
Autor:
van der Loo, Mark P. J.
It is often useful to tap information from a running R script. Obvious use cases include monitoring the consumption of resources (time, memory) and logging. Perhaps less obvious cases include tracking changes in R objects orcollecting output of unit
Externí odkaz:
http://arxiv.org/abs/2002.07472
Publikováno v:
Journal of Statistical Software 97 (10) (2021)
Checking data quality against domain knowledge is a common activity that pervades statistical analysis from raw data to output. The R package 'validate' facilitates this task by capturing and applying expert knowledge in the form of validation rules:
Externí odkaz:
http://arxiv.org/abs/1912.09759
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.