Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 10 of 10 for “"itemset"”.
-
A Fast Minimal Infrequent Itemset Mining Algorithm
A novel fast algorithm for finding quasi identifiers in large datasets is presented. Performance measurements on a broad range of datasets demonstrate substantial reductions in run-time relative to the state of the art and the scalability of the algorithm to realistically-sized datasets up to …
-
A distributed approach to Frequent Itemset Mining at low support levels
Frequent Itemset Mining, the process of finding frequently co-occurring sets of items in a dataset, has been at the core of the field of data mining for the past 25 years. During this time the datasets have grown much faster than the algorithms capacity to process them. Great progress was made at …
-
Scaling data mining activities on very large datasets
… emphasis on association rule and frequent itemset mining. In particular, it proposes a scalable itemset mining approach relying on (i) a persistent (disk-based) representation of the transactional data, (ii) ad-hoc data retrieval techniques, and (iii)~strategies for the integration of …
-
Data mining with bilattices
… most of the works focuses on finding patterns on itemsets, especially associations between items. With the fast development of high technologies and large scale of information collection tools, the need for data mining has gone far beyond association mining. In this thesis, a new framework is …
-
Strip-Miner: Automatic Bug Detection in Large Software Code with Low False Positive Rate
… of code with a data mining technique "frequent itemset mining" to reduce the false positive rate. We adopt a two phase approach 1) finding the potential bugs and 2) filtering the false positive ones. In the first phase we extract code elements and dependencies among them using static analysis …
-
New Approaches to Frequent and Incremental Frequent Pattern Mining
… mining.</p> <p>One of the challenges of frequent itemset mining is long running times of the algorithms. Two major costs of long running times of frequent itemset mining are due to the number of database scans and the number of candidates generated (the latter one requires memory, and the more the …
-
API Knowledge Guided Test Generation for Machine Learning Libraries
… the API documents. Then, we use the frequent itemset mining technique to mine the API usage patterns from a large corpus of machine learning API related code fragments collected from SO. Finally, we use the above two types of API knowledge to guide the test generation of existing test …
-
Learning lost temporal fuzzy association rules
… (FRBS). The combination of temporal, fuzzy and itemset space was simultaneously searched with a genetic algorithm (GA) to overcome the problem. The framework transforms the dataset to a graph for efficiently searching the dataset. A choice of model in fuzzy representation provides a trade-off in …
-
Modeling and Analysis of Regulatory Elements in Arabidopsis thaliana from Annotated Genomes and Gene Expression Data
… maximal bicliques of genes and motifs, called itemsets. An itemset consists of a set of genes (called a geneset) and a set of motifs (called a motifset) such that every motif in the motifset occurs in the promoter of every gene in the geneset. XcisClique differs from existing tools of the same …