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Privacy wizards for social networking sites
TLDR
A template for the design of a social networking privacy wizard based on an active learning paradigm called uncertainty sampling, which is able to recommend high-accuracy privacy settings using less user input than existing policy-specification tools. Expand
Enhancing text clustering by leveraging Wikipedia semantics
TLDR
A way to build a concept thesaurus based on the semantic relations (synonym, hypernym, and associative relation) extracted from Wikipedia is proposed and a unified framework to leverage these semantic relations in order to enhance traditional content similarity measure for text clustering is developed. Expand
Finding related tables
TLDR
This work considers the problem of finding related tables in a large corpus of heterogenous tables and proposes a framework that captures several types of relatedness, including tables that are candidates for joins and tables that is candidates for union. Expand
REX: Explaining Relationships between Entity Pairs
TLDR
REX is presented, a system that takes a pair of entities in a given knowledge base as input and efficiently identifies a ranked list of relationship explanations, which formally define relationship explanations and analyze their desirable properties. Expand
Look who I found: understanding the effects of sharing curated friend groups
TLDR
The impact that circle-sharing has had on the growth and structure of the Google+ social network is investigated and features that can be used to predict which of a user's circles (s)he is most likely to share are identified, demonstrating that it is feasible to suggest to a user which circles to share with friends. Expand
Maximal planar scale-free Sierpinski networks with small-world effect and power law strength-degree correlation
Many real networks share three generic properties: they are scale-free, display a small-world effect, and show a power law strength-degree correlation. In this paper, we propose a type ofExpand
A privacy recommendation wizard for users of social networking sites
TLDR
A machine learning privacy wizard, or recommendation tool, that is based on the underlying observation that real users conceive their privacy preferences based on an implicit structure and can be used to recommend detailed privacy settings for the user. Expand
Analytical solution of average path length for Apollonian networks.
TLDR
With the help of recursion relations derived from the self-similar structure, the rigorous solution shows that the average path length grows logarithmically as d[over ]_(t) proportional, variantln N_(T) in the infinite limit of network size N_( t) . Expand
Recursive weighted treelike networks
Abstract.We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which areExpand
Splash: ad-hoc querying of data and statistical models
Data mining is increasingly performed by people who are not computer scientists or professional programmers. It is often done as an iterative process involving multiple ad-hoc tasks, as well as dataExpand
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