Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Tsourakakis, Charalampos"'
Functional dependencies (FDs) are a central theme in databases, playing a major role in the design of database schemas and the optimization of queries. In this work, we introduce the {\it targeted least cardinality candidate key problem} (TCAND). Thi
Externí odkaz:
http://arxiv.org/abs/2408.13540
Autor:
Tsourakakis, Charalampos E.
A central task in network analysis is to identify important nodes in a graph. Betweenness centrality (BC) is a popular centrality measure that captures the significance of nodes based on the number of shortest paths each node intersects with. In this
Externí odkaz:
http://arxiv.org/abs/2408.01157
In 1907, Sir Francis Galton independently asked 787 villagers to estimate the weight of an ox. Although none of them guessed the exact weight, the average estimate was remarkably accurate. This phenomenon is known as wisdom of crowds. In a clever exp
Externí odkaz:
http://arxiv.org/abs/2406.07805
This study introduces a novel approach for learning mixtures of Markov chains, a critical process applicable to various fields, including healthcare and the analysis of web users. Existing research has identified a clear divide in methodologies for l
Externí odkaz:
http://arxiv.org/abs/2405.15094
Sequential data naturally arises from user engagement on digital platforms like social media, music streaming services, and web navigation, encapsulating evolving user preferences and behaviors through continuous information streams. A notable unreso
Externí odkaz:
http://arxiv.org/abs/2402.17730
In this work, we introduce a novel evaluation framework for generative models of graphs, emphasizing the importance of model-generated graph overlap (Chanpuriya et al., 2021) to ensure both accuracy and edge-diversity. We delineate a hierarchy of gra
Externí odkaz:
http://arxiv.org/abs/2312.03691
Dense subgraph discovery methods are routinely used in a variety of applications including the identification of a team of skilled individuals for collaboration from a social network. However, when the network's node set is associated with a sensitiv
Externí odkaz:
http://arxiv.org/abs/2306.02338
Publikováno v:
In Proceedings of the ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS) 2023
We design the first node-differentially private algorithm for approximating the number of connected components in a graph. Given a database representing an $n$-vertex graph $G$ and a privacy parameter $\varepsilon$, our algorithm runs in polynomial t
Externí odkaz:
http://arxiv.org/abs/2304.05890
A large number of modern applications ranging from listening songs online and browsing the Web to using a navigation app on a smartphone generate a plethora of user trails. Clustering such trails into groups with a common sequence pattern can reveal
Externí odkaz:
http://arxiv.org/abs/2302.04680
Benford's law describes the distribution of the first digit of numbers appearing in a wide variety of numerical data, including tax records, and election outcomes, and has been used to raise "red flags" about potential anomalies in the data such as t
Externí odkaz:
http://arxiv.org/abs/2205.13426