Physical Sciences and Mathematics Commons^™

Detecting Malicious Software By Dynamicexecution, Jianyong Dai

Electronic Theses and Dissertations

Traditional way to detect malicious software is based on signature matching. However, signature matching only detects known malicious software. In order to detect unknown malicious software, it is necessary to analyze the software for its impact on the system when the software is executed. In one approach, the software code can be statically analyzed for any malicious patterns. Another approach is to execute the program and determine the nature of the program dynamically. Since the execution of malicious code may have negative impact on the system, the code must be executed in a controlled environment. For that purpose, we have …

Effects Of Similarity Metrics On Document Clustering, Rushikesh Veni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Document clustering or unsupervised document classification is an automated process of grouping documents with similar content. A typical technique uses a similarity function to compare documents. In the literature, many similarity functions such as dot product or cosine measures are proposed for the comparison operator.

For the thesis, we evaluate the effects a similarity function may have on clustering. We start by representing a document and a query, both as a vector of high-dimensional space corresponding to the keywords followed by using an appropriate distance measure in k-means to compute similarity between the document vector and the query vector to …

Parallel Mining Of Association Rules Using A Lattice Based Approach, Wessel Morant Thomas

CCE Theses and Dissertations

The discovery of interesting patterns from database transactions is one of the major problems in knowledge discovery in database. One such interesting pattern is the association rules extracted from these transactions. Parallel algorithms are required for the mining of association rules due to the very large databases used to store the transactions. In this paper we present a parallel algorithm for the mining of association rules. We implemented a parallel algorithm that used a lattice approach for mining association rules. The Dynamic Distributed Rule Mining (DDRM) is a lattice-based algorithm that partitions the lattice into sublattices to be assigned to …

Investigating Data Mining Techniques For Extracting Information From Alzheimer's Disease Data, Vinh Quoc Dang

Theses : Honours

Data mining techniques have been used widely in many areas such as business, science, engineering and more recently in clinical medicine. These techniques allow an enormous amount of high dimensional data to be analysed for extraction of interesting information as well as the construction of models for prediction. One of the foci in health related research is Alzheimer's disease which is currently a non-curable disease where diagnosis can only be confirmed after death via an autopsy. Using multi-dimensional data and the applications of data mining techniques, researchers hope to find biomarkers that will diagnose Alzheimer's disease as early as possible. …

Bootstrapping Events And Relations From Text, Ting Liu

Legacy Theses & Dissertations (2009 - 2024)

Information Extraction (IE) is a technique for automatically extracting structured data from text documents. One of the key analytical tasks is extraction of important and relevant information from textual sources. While information is plentiful and readily available, from the Internet, news services, media, etc., extracting the critical nuggets that matter to business or to national security is a cognitively demanding and time consuming task. Intelligence and business analysts spend many hours poring over endless streams of text documents pulling out reference to entities of interest (people, locations, organizations) as well as their relationships as reported in text. Such extracted "information …