Results 1 - 10
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160
A.: Mining graph evolution rules
- In: ECML/PKDD
, 2009
"... Abstract. In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequence of snapshots of an evolving graph, we aim at discovering rules describing the local changes occurring in it. ..."
Abstract
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Cited by 37 (4 self)
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Abstract. In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequence of snapshots of an evolving graph, we aim at discovering rules describing the local changes occurring in it
Materials for an exploratory theory of the network society.
- The British Journal of Sociology
, 2000
"... ABSTRACT This article aims at proposing some elements for a grounded theor y of the network society. The network society is the social structure characteristic of the Information Age, as tentatively identi ed by empirical, cross-cultural investigation. It permeates most societies in the world, in v ..."
Abstract
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Cited by 122 (0 self)
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of ows. And so to do an increasing number of alternative social practices (such as social movements) and personal interaction networks. However, the space of ows does include a territorial dimension, as it requires a technological infrastructure that operates from certain locations, and as it connects
Ontology-Aware Classification and Association Rule Mining for Interest and Link Prediction in Social Networks
"... Previous work on analysis of friendship networks has identified ways in which graph features can be used for prediction of link existence and persistence, and shown that features of user pairs such as shared interests can marginally improve the precision and recall of link prediction. This marginal ..."
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Cited by 3 (0 self)
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using interest data. A test bed previously developed using the social network and weblogging service LiveJournal is extended using this integrative approach. Our results show how this semantically integrative approach to link mining yields a boost in precision and recall of known friendships when
FDM Secure Mining of Association Rules in Horizontally Distributed Databases
"... We study the problem of privacy-preservation in social networks. We consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about link ..."
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We study the problem of privacy-preservation in social networks. We consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about
Beyond streams and graphs: Dynamic tensor analysis
- In KDD
, 2006
"... How do we find patterns in author-keyword associations, evolving over time? Or in DataCubes, with product-branchcustomer sales information? Matrix decompositions, like principal component analysis (PCA) and variants, are invaluable tools for mining, dimensionality reduction, feature selection, rule ..."
Abstract
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Cited by 113 (16 self)
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How do we find patterns in author-keyword associations, evolving over time? Or in DataCubes, with product-branchcustomer sales information? Matrix decompositions, like principal component analysis (PCA) and variants, are invaluable tools for mining, dimensionality reduction, feature selection, rule
Improved Association Rule Hiding Algorithm for Privacy Preserving Data Mining
"... Abstract: -the main objective of data mining is to extract previously unknown patterns from large collection of data. With the rapid growth in hardware, software and networking technology there is outstanding growth in the amount data collection. Organizations collect huge volumes of data from hete ..."
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individuals. The original data is modified or a process is used in such a way that private data and private knowledge remain private even after the mining process. The objective of this paper is to implement an improved association rule hiding algorithm for privacy preserving data mining. This paper compares
Privacy Preserving Data Mining Using Association Rule With Condensation Approach
"... Abstract—With the rapid development data mining within various fields and security and privacy concerns come into view. In data mining while releasing micro-data or patterns from large databases individual or organizational private data may get compromise the information. The main aim behind privacy ..."
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multiparty computation) securely transferring data over the network with hiding process which hide sensitive association rule which create threat to privacy. Now privacy preserving data mining has become increasingly popular because it provides sharing of private or sensitive data for analysis purposes. Most
Social Media Data Mining: A Social Network Analysis Of Tweets During . . .
, 2011
"... Using tweets extracted from Twitter during the Australian 2010-2011 floods, social network analysis techniques were used to generate and analyse the online networks that emerged at that time. The aim was to develop an understanding of the online communities for the Queensland, New South Wales and Vi ..."
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(mainly the Queensland Police Services), political personalities (Queensland Premier, Prime Minister, Opposition Leader, Member of Parliament), social media volunteers, traditional media reporters, and people from not-for-profit, humanitarian, and community associations. A range of important resources
14 Protecting Private Information in Online Social Networks
"... Abstract. Because personal information can be inferred from associations with friends, privacy becomes increasingly important as online social network services gain more popularity. Our recent study showed that the causal relations among friends in social networks can be modeled by a Bayesian networ ..."
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Abstract. Because personal information can be inferred from associations with friends, privacy becomes increasingly important as online social network services gain more popularity. Our recent study showed that the causal relations among friends in social networks can be modeled by a Bayesian
Finding Social Network for Trust Calculation
- In proc. ECAI2004
, 2004
"... Abstract. Trust is a necessary concept to realize the Semantic Web. But how can we build a “Web of Trust”? We first argue that a small “Web of Trust ” for each community is very essential to realize a huge “Web of Trust. ” Then, we focus on an academic community as a microcosm of a “Web of Trust ” a ..."
Abstract
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Cited by 21 (3 self)
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” and show a web mining approach to generate a social network automatically. Each edge is added using the number of retrieved pages by a search engine which includes both persons ’ names. Moreover, each edge is given a label, such as “coauthors” or “members of the same project, ” by applying classification
Results 1 - 10
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160