On Chinese and Western Family Trees: Mechanism and Performance

Family tree is an efficient data structure to store the kinship information in a family. There are basically two kinds of trees: Western Family Tree (WFT) and Oriental Family Tree such as Chinese Family Tree (CFT). To get an insight of their efficiency in the context of family kinship presentation and information extraction, in this paper we develop WFT and CFT presentation models and search algorithms, comparing their search performance and inherent mechanism. The study reveals that the computational cost is higher in CFT model, but it provides a greater gain in information retrieval and produces more details of the kinship between individuals in the family

NodeTrix: Hybrid Representation for Analyzing Social Networks

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily answer the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections from either a node-link or a matrix, flexibly manipulate the NodeTrix representation to explore the dataset, and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results