A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Multi-Sorted Inverse Frequent Itemsets Mining: On-Going Research
2016
Alberto Mendelzon Workshop on Foundations of Data Management
Preserved Fulltext
Inverse frequent itemset mining (IFM) consists of generating artificial transactional databases reflecting patterns of real ones, in particular, satisfying given frequency constraints on the itemsets. ...
Given R, Σ = Σ ∪ Σ, and an integer size > 0, the multi-sorted inverse frequent itemset mining problem, shortly denoted as ms-IFM, consists of finding a many-sorted dataset D on R such that both δ D = size ...
In this paper we propose to extend inverse frequent itemset mining (IFM) that consists of generating a transactional database satisfying given support constraints on the itemsets in an input set, that ...
dblp:conf/amw/SaccaSP16
fatcat:zi5k2eyzszbevbongwhrsmmjqu
Multi-Sorted Inverse Frequent Itemsets Mining
[article]
2013
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
on the itemsets in an input set, that are typically the frequent ones. ...
A first step in this direction is to use inverse mining techniques such as inverse frequent itemset mining (IFM) that consists of generating a transactional database satisfying given support constraints ...
IFM Problem In this section we provide a general formulation of the many-sorted inverse frequent itemsets mining problem. ...
arXiv:1310.3939v1
fatcat:aj54nykpfzakbkenmpl63fx3fy
Output privacy in data mining
2011
ACM Transactions on Database Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
This paper presents a systematic study on the problem of protecting output privacy in data mining, and particularly, stream mining: (i) we highlight the importance of this problem by showing that even ...
In general, privacy preservation in data mining demands protecting both input and output privacy: the former refers to sanitizing the raw data itself before performing mining; while the latter refers to ...
ACKNOWLEDGEMENTS This work is partially sponsored by grants from NSF CyberTrust, NSF NetSE, an IBM SUR grant, and a grant from Intel Research Council. ...
doi:10.1145/1929934.1929935
fatcat:hjxhddlkr5fcrdafcx4gyzgjcy
Mining@home: toward a public-resource computing framework for distributed data mining
2009
Concurrency and Computation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In particular, we focus on one of the main data mining problems: the extraction of closed frequent itemsets from transactional databases. ...
This paper introduces a general framework for distributed data mining applications called Mining@home. ...
ACKNOWLEDGEMENTS This research work has been partially carried out under the Network of Excellences CoreGRID (FP6 contract no. IST-FP6-004265) and S-Cube (FP7 contract no. ...
doi:10.1002/cpe.1545
fatcat:2ccaq3kjpvbnjmaqexmxdzruya
Mining Frequent Itemsets: a Formal Unification
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
It is generally well agreed that developing a unifying theory is one of the most important issues in Data Mining research. ...
In the last two decades, a great deal of work has been devoted to the algorithmic aspects of the Frequent Itemset (FI) Mining problem. We are motivated by the need for formal modeling in the field. ...
INTRODUCTION Mining Frequent Itemsets (FI) is an important problem in Data Mining (DM). ...
arXiv:1502.02642v4
fatcat:5jryhi5fcvcudo2wti5dknnwbm
Butterfly: Protecting Output Privacy in Stream Mining
2008
2008 IEEE 24th International Conference on Data Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
This work studies the problem of protecting output privacy in the context of frequent pattern mining over data streams. ...
Privacy preservation in data mining demands protecting both input and output privacy. The former refers to sanitizing the raw data itself before performing mining. ...
ACKNOWLEDGMENT This research is partially sponsored by grants from NSF CyberTrust, an IBM SUR grant, and an IBM faculty award. ...
doi:10.1109/icde.2008.4497526
dblp:conf/icde/WangL08
fatcat:flw4m2t2nfgfxlz4jcqublizde
Frequent Itemset Mining and Multi-Layer Network-Based Analysis of RDF Databases
2021
Mathematics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The results confirm that frequent itemset mining provides an informative sampled subsets of RDF databases which can be simultaneously analysed as layers of a multilayer network. ...
The method utilises frequent itemset mining (FIM) of the subjects, predicates and the objects of the RDF data, and automatically extracts informative subsets of the database for the analysis. ...
Frequent Itemset Mining in Multidimensional Networks Frequent itemset mining (FIM) is a mining technique used to uncover frequent correlations in transactional datasets [48] . ...
doi:10.3390/math9040450
fatcat:w2kbidjmqbhjhneoikfl3gvv2m
MITHRIL: Mining Sporadic Associations for Cache Prefetching
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
MITHRIL is inspired by sporadic association rule mining and only relies on the timestamps of requests. ...
The growing pressure on cloud application scalability has accentuated storage performance as a critical bottle- neck. ...
Sporadic Association Rule Mining Frequent itemset mining aims to discover which items co-occur frequently in a transaction database. ...
arXiv:1705.07400v1
fatcat:zoj7chgrore7poh62jqfeqlrwu
EBPA: An efficient data structure for frequent closed itemset mining
2013
Applied Mathematical Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Practically, many data structures were proposed to maintain valuable data for frequent closed itemset mining (FCIM), while each data structure has its own advantages and disadvantages. ...
In closed itemset mining, the process of mining from a large transaction database directly often leads to inefficient space and time. ...
EBPA: an efficient data structure for frequent closed itemset mining ...
doi:10.12988/ams.2013.13135
fatcat:qrmnxy62ifdhdfi6tpfckat2sa
Semantic Pattern Mining Based Web Service Recommendation
[chapter]
2016
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
We define the notion of semantic patterns which are maximal frequent itemsets of topics. ...
These sets of services are then used to recommend services in the on-line process. ...
We propose a content-based recommendation system leveraging probabilistic topic models and pattern mining (more precisely, maximal frequent itemset mining). ...
doi:10.1007/978-3-319-46295-0_26
fatcat:pkuqakkbongabdzp5cho4pbbuq
TopCat: data mining for topic identification in a text corpus
2004
IEEE Transactions on Knowledge and Data Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
Frequent itemsets are generated from the groups of items, followed by clusters formed with a hypergraph partitioning scheme. ...
This paper presents a novel method for identifying related items based on "traditional" data mining techniques. ...
Frequent itemset computation Computing frequent itemsets to 76 minutes. ...
doi:10.1109/tkde.2004.32
fatcat:kogmhh2ubrbyjktl32qaalxz6e
TopCat: Data Mining for Topic Identification in a Text Corpus
[chapter]
1999
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
Frequent itemsets are generated from the groups of items, followed by clusters formed with a hypergraph partitioning scheme. ...
This paper presents a novel method for identifying related items based on "traditional" data mining techniques. ...
Frequent itemset computation Computing frequent itemsets to 76 minutes. ...
doi:10.1007/978-3-540-48247-5_19
fatcat:ut3lq3fjcndvhbjixwfgszx4ve
An information-theoretic approach to quantitative association rule mining
2007
Knowledge and Information Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2013; you can also visit the original URL.
The file type is application/pdf.
We find that the cliques in the MI graph represent a majority of the frequent itemsets. ...
Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and the usefulness of association rules ...
As an on-going work, we consider to incorporate the concept of nearclique, which is a clique except for one edge, for computing frequent itemsets into our framework. ...
doi:10.1007/s10115-007-0104-4
fatcat:6scsfelcxrernbmdoit36yfoze
Discovering Strategic Behaviors in Multi-Agent Scenarios by Ontology-Driven Mining
[chapter]
2008
Advances in Robotics, Automation and Control
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Next, L 1 is used to find the set of frequent 2-itemsets L 2 , and so on until all the frequent patterns have been discovered. ...
Apriori has been the first frequent itemset algorithm to be proposed (Agrawal et al., 1994) . It exploits a bottom-up, level-wise exploration of the lattice of frequent itemsets. ...
Discovering Strategic Behaviors in Multi-Agent Scenarios by Ontology-Driven Mining, Advances in Robotics, Automation and Control, Jesus Aramburo and Antonio Ramirez Trevino (Ed.), ISBN: 978-953-7619-16 ...
doi:10.5772/5529
fatcat:qkacis2w7zdplczbk7clpmgbba
Heavyweight Pattern Mining in Attributed Flow Graphs
2014
2014 IEEE International Conference on Data Mining
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The principle of strategy is from one thing, to know ten thousand things." -Miyamoto Musashi, in The Book of Five Rings. ...
If you master the principles of sword-fencing, when you freely beat one man, you beat any man in the world. The spirit of defeating a man is the same for ten million men. ...
In frequent-itemset mining, the more frequent an itemset is in the database, the more interesting the itemset is considered to be. ...
doi:10.1109/icdm.2014.51
dblp:conf/icdm/GomesASSD14
fatcat:kvxyxu6mbvb73pqj4fpez6h5o4
« Previous
Showing results 1 — 15 out of 263 results