Search results for: David J. Haglin
chapter
In this work we propose a novel formulation that models the attack and compromise on a cyber network as a combination of two parts — direct compromise of a host and the compromise occurring through the spread of the attack on the network from a compromised host. The model parameters for the nodes are a concise representation of the host profiles that can include the risky behaviors of the associated...
chapter
A recent trend in hardware development is producing computing systems that are stretching the number of cores and size of shared-memory beyond where most fundamental serial algorithms perform well. The expectation is that this trend will continue. So it makes sense to rethink our fundamental algorithms such as sorting. There are many situations where data that needs to be sorted will actually fit...
chapter
Graph mining algorithms that seek to find interesting structure in a graph are compelling for many reasons but may not lead to useful information learned from the data. This position paper explores the current graph mining approaches and suggests why certain algorithms may provide misleading information whereas others may be just what is needed. In particular, algorithms that ignore the rich set of...
chapter
A key challenge to automated clustering of documents in large text corpora is the high cost of comparing documents in a multi-million dimensional document space. The Anchors Hierarchy is a fast data structure and algorithm for localizing data based on a triangle inequality obeying distance metric, the algorithm strives to minimize the number of distance calculations needed to cluster the documents...
chapter
Two of the most commonly used hashing strategies-linear probing and hashing with chaining-are adapted for efficient execution on a Cray XMT. These strategies are designed to minimize memory contention. Datasets that follow a power law distribution cause significant performance challenges to shared memory parallel hashing implementations. Experimental results show good scalability up to 128 processors...
article
Data Mining and Knowledge Discovery > 2008 > 16 > 2 > 165-196
A new algorithm, SUDA2, is presented which finds minimally unique itemsets i.e., minimal itemsets of frequency one. These itemsets, referred to as Minimal Sample Uniques (MSUs), are important for statistical agencies who wish to estimate the risk of disclosure of their datasets. SUDA2 is a recursive algorithm which uses new observations about the properties of MSUs to prune and traverse the search...
