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We present a new approach to matching graphs embedded in R2 or R3. Unlike earlier methods, our approach does not rely on the similarity of local appearance features, does not require an initial alignment, can handle partial matches, and can cope with non-l ...
A tangle is a graph drawn in the plane so that any pair of edges have precisely one point in common, and this point is either an endpoint or a point of tangency. If we allow a third option: the common point may be a proper crossing between the two edges, t ...
With the tremendous growth of social networks, there has been a growth in the amount of new data that is being created every minute on these networking sites. Twitter acts as a great source of rich information for millions of users on the internet and ther ...
Artificial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. In this paper we introduce the concept of terminal graph (t-graph for short), w ...
A method of data retrieval from a data repository in response to a query having either list of keywords and/or list of attribute-value pairs, the method comprising the steps of: providing an inverted index generated from the data repository, the inverted i ...
We present the results of group dynamics and their effect on success in problem solving / decision making meetings. We use a novel multiple input environment for collaboration and data collection, and a hidden profile task given to groups, whose goals are ...
This lecture introduces systematically into the problem of managing large data collections in peer-to-peer systems. Search over large datasets has always been a key problem in peer-to-peer systems and the peer-to-peer paradigm has incited novel directions ...
We design two different strategies for computing the unknown content preferences in an online social network based on a small set of nodes in the corresponding social graph for which this information is available ahead of time. The techniques take advantag ...
Mobile phone data provides rich dynamic information on human activities in social network analysis. In this paper, we represent data from two different modalities as a graph and functions defined on the vertex set of the graph. We propose a regularization ...
Implementing machine learning algorithms for large data, such as the Web graph and social networks, is challenging. Even though much research has focused on making sequential algorithms more scalable, their running times continue to be prohibitively long. ...