Michael T. Goodrich

TL;DR: New applications of the nearest-neighbor chain algorithm are shown, a technique that originated in agglomerative hierarchical clustering and applies to a diverse class of geometric problems.

TL;DR: In this paper, the authors introduce a network property called membership dimension, which characterizes the cognitive load required to maintain relationships between participants and categories in a social network, and show that any connected network has a system of categories that will support greedy routing, but that these categories can be made to have small membership dimension if and only if the underlying network exhibits the small-world phenomenon.

TL;DR: In this paper, the authors combine the idea of confluent drawings with Sugiyama style drawings, in order to reduce the edge crossings in the resultant drawings, and it is easier to understand the structures of graphs from the mixed style drawings.

TL;DR: This work considers how to allow for redundant insertions, deletions, and updates, as well as operations based on the ranks of data items, such as Extract (j), which simultaneously selects and deletes the jth smallest data item.

TL;DR: This paper gives a provably optimal-cost dynamic programming algorithm for gerrymandering on a single range query attribute and proposes a family of heuristics on multiple range query attributes for this problem: with range queries and point updates.