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Predicting missing links via local information
TLDR
A new similarity measure, motivated by the resource allocation process taking place on networks, is proposed and shown to have higher prediction accuracy than common neighbours, which can remarkably enhance the prediction accuracy.
Bipartite network projection and personal recommendation.
TLDR
This work provides a creditable method for compressing bipartite networks, and highlights a possible way for the better solution of a long-standing challenge in modern information science: How to do a personal recommendation.
Solving the apparent diversity-accuracy dilemma of recommender systems
TLDR
This paper introduces a new algorithm specifically to address the challenge of diversity and shows how it can be used to resolve this apparent dilemma when combined in an elegant hybrid with an accuracy-focused algorithm.
Leaders in Social Networks, the Delicious Case
TLDR
It is shown that LeaderRank outperforms PageRank in terms of ranking effectiveness, as well as robustness against manipulations and noisy data, which suggest that leaders who are aware of their clout may reinforce the development of social networks, and thus the power of collective search.
Toward link predictability of complex networks
TLDR
A quantitative index for measuring link predictability and an algorithm that outperforms state-of-the-art link prediction methods in both accuracy and universality are introduced and a universal structural consistency index is proposed that is free of prior knowledge of network organization.
Minority Games: Interacting agents in financial markets
The Minority Game is a physicist's attempt to explain market behaviour by the interaction between traders. With a minimal set of ingredients and drastic assumptions, this model reproduces market
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