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Mining top-K high utility itemsets (KDD 2012)
 
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Mining top-K high utility itemsets KDD 2012 Cheng Wei Wu Bai-En Shie Vincent S. Tseng Philip S. Yu Mining high utility itemsets from databases is an emerging topic in data mining, which refers to the discovery of itemsets with utilities higher than a user-specified minimum utility threshold min_util. Although several studies have been carried out on this topic, setting an appropriate minimum utility threshold is a difficult problem for users. If min_util is set too low, too many high utility itemsets will be generated, which may cause the mining algorithms to become inefficient or even run out of memory. On the other hand, if min_util is set too high, no high utility itemset will be found. Setting appropriate minimum utility thresholds by trial and error is a tedious process for users. In this paper, we address this problem by proposing a new framework named top-k high utility itemset mining, where k is the desired number of high utility itemsets to be mined. An efficient algorithm named TKU (Top-K Utility itemsets mining) is proposed for mining such itemsets without setting min_util. Several features were designed in TKU to solve the new challenges raised in this problem, like the absence of anti-monotone property and the requirement of lossless results. Moreover, TKU incorporates several novel strategies for pruning the search space to achieve high efficiency. Results on real and synthetic datasets show that TKU has excellent performance and scalability.
MINING HIGH UTILITY ITEM SETS IN TRANSACTIONAL DATABASE
 
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Data mining is the process of revealing nontrivial,previously unknown and potentially useful information from large databases. Discovering useful patterns hidden in the database plays an essential role in several data mining tasks,such as frequent pattern mining, weighted pattern mining and high utility pattern mining. This Project aims at mining the different combination of itemsets with high utility like profits from the transactional database. Utility based data mining is a new research area interested in all types of utility factors in data mining processes and targeted at incorporating utility considerations in data mining tasks. The UMining algorithm is used to find all high utility itemsets within the given utility constraint threshold. This algorithm has a pruning strategy of its own. Fast Utility Mining is a novel algorithm which is faster and simpler than the original UMining algorithm for generating high utility itemsets. The experimental evaluation on artificial datasets show that this algorithm executes faster than UMining algorithm. Another algorithm, Fast Utility Frequent Mining, is a more precise and very recent algorithm. It takes both the utility and the support measure into consideration.
Views: 798 Deepika Starz
Efficient Algorithms for Mining Top-K High Utility Itemsets
 
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Efficient Algorithms for Mining Top-K High Utility Itemsets TO GET THIS PROJECT IN ONLINE OR THROUGH TRAINING SESSIONS CONTACT: Chennai Office: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai – 83. Landmark: Next to Kotak Mahendra Bank / Bharath Scans. Landline: (044) - 43012642 / Mobile: (0)9952649690 Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry – 9. Landmark: Opp. To Thattanchavady Industrial Estate & Next to VVP Nagar Arch. Landline: (0413) - 4300535 / Mobile: (0)8608600246 / (0)9952649690 Email: [email protected], Website: http://www.jpinfotech.org, Blog: http://www.jpinfotech.blogspot.com High utility itemsets (HUIs) mining is an emerging topic in data mining, which refers to discovering all itemsets having a utility meeting a user-specified minimum utility threshold min_util. However, setting min_util appropriately is a difficult problem for users. Generally speaking, finding an appropriate minimum utility threshold by trial and error is a tedious process for users. If min_util is set too low, too many HUIs will be generated, which may cause the mining process to be very inefficient. On the other hand, if min_util is set too high, it is likely that no HUIs will be found. In this paper, we address the above issues by proposing a new framework for top-k high utility itemset mining, where k is the desired number of HUIs to be mined. Two types of efficient algorithms named TKU (mining Top-K Utility itemsets) and TKO (mining Top-K utility itemsets in One phase) are proposed for mining such itemsets without the need to set min_util. We provide a structural comparison of the two algorithms with discussions on their advantages and limitations. Empirical evaluations on both real and synthetic datasets show that the performance of the proposed algorithms is close to that of the optimal case of state-of-the-art utility mining algorithms.
Views: 1110 jpinfotechprojects
Efficient Algorithms for mining high utility itemsets from transactional databases
 
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Final year project based on data mining
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a fast high utility itemsets mining algorithm
 
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Subscribe today and give the gift of knowledge to yourself or a friend a fast high utility itemsets mining algorithm
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Final Year Projects | Efficient Algorithms for Mining High Utility Itemsets from Transactional
 
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IEEE Projects 2012 | Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases More Details: Visit http://clickmyproject.com/a-secure-erasure-codebased-cloud-storage-system-with-secure-data-forwarding-p-128.html Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
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Efficient Algorithms for Mining Top K High Utility Itemsets
 
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2016 IEEE Transaction on Knowledge and Data Engineering For More Details::Contact::K.Manjunath - 09535866270 http://www.tmksinfotech.com and http://www.bemtechprojects.com 2016 and 2017 IEEE @ TMKS Infotech,Bangalore
Views: 815 manju nath
Efficient Algorithms for Mining Top - K High  Utility Itemsets | Final Year projects 2016
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
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Efficient Algorithms Mining Top-K High Utility Itemsets | Final Year Projects 2016 - 2017
 
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Final Year Projects | Efficient Algorithms for Mining High Utility Itemsets
 
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Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 291 Clickmyproject
Efficient Vertical Mining of High Average-Utility Itemsets based on Novel Upper-Bounds
 
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Efficient Algorithms for Mining Top-K High Utility Itemsets | Final Year Projects 2016 - 2017
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://myprojectbazaar.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/myprojectbazaar Mail Us: [email protected]
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Efficient Algorithm for mining high utility itemsets from transactional databases
 
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You can influence the mining performance more easily from transactional databases.
Views: 299 Surendar B
Efficient Algorithms for Mining Top -K High Utility Itemsets | Final Year Projects 2016 - 2017
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://myprojectbazaar.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/myprojectbazaar Mail Us: [email protected]
Views: 27 MyProjectBazaar
Mining High Utility Patterns Using D2HUP Algorithm
 
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Mining High Utility Patterns Using D2HUP Algorithm Platform: Data Mining (Java) NetBeans IDE 8.1/8.2 Server: Glassfish Server
Views: 62 K R I ShNa V
Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases new
 
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Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases Abstract—Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. Such a large number of candidate itemsets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility itemsets. In this paper, we propose two algorithms, namely utility pattern growth (UP-Growth) and UP-Growth+, for mining high utility itemsets with a set of effective strategies for pruning candidate itemsets. The information of high utility itemsets is maintained in a tree-based data structure named utility pattern tree (UP-Tree) such that candidate itemsets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP-Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic data sets. Experimental results show that the proposed algorithms, especially UPGrowth+, not only reduce the number of candidates effectively but also outperform other algorithms substantially in terms of runtime, especially when databases contain lots of long transactions.
Views: 184 Projectsgoal
IEEE Projects | Efficient Mining of Frequent Itemsets on Large Uncertain Databases
 
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IEEE Projects | Efficient Mining of Frequent Itemsets on Large Uncertain Databases More Details: Visit http://clickmyproject.com/a-secure-erasure-codebased-cloud-storage-system-with-secure-data-forwarding-p-128.html Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 530 Clickmyproject
HEURISTICS RULES BASED MINING HIGH UTILITY ITEMSETS FROM TRANSACTIONAL DATABASE
 
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Mining frequent itemsets is an active area in data mining that aims at searching interesting relationships between items in databases. It can be used to address to a wide variety of problems such as discovering association rules, sequential patterns, correlations and much more. A transactional database is a data set of transactions, each composed of a set of items, called an itemset (frequently occurring in a database). Existing methods often generate a huge set of potential high utility item sets and their mining performance is degraded consequently. There is a lacking of mining performance with these huge number of potential high utility itemsets; higher processing Time too. Two novel algorithms as well as a compact data structure for efficiently discovering high utility itemsets are proposed. High utility itemsets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree). Implementing mining process through Discarding Local Unpromising Items and Decreasing Local Node Utilities strategies. An experimental result predicts that not only reduces the number of candidates effectively but also outperforms other algorithms DIVYA BHARATHY.M (VMC 791) Department of Master of Computer Applications Veltech Multi Tech Engg College.
Views: 303 Divya Bharathy
Efficient Algorithms for Mining Top-K High  Utility Itemsets | Final Year Projects 2016
 
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Efficient Vertical Mining of High Average Utility Itemsets - IEEE PROJECTS 2018
 
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Efficient Algorithms for Mining the Concise and Lossless Representation of High Utility Itemsets
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 66 Clickmyproject
Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases
 
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Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases
 
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Projects Goal is provide final year projects for it, ieee final year projects, final year it projects, m tech projects in pune,computer engineering projects for final year students, internship in pune for engineering students, matlab projects for engineering students. http://www.projectsgoal.com/data-mining/
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Efficient Algorithms For Mining High Utility Itemsets From Transactional Databases
 
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Efficient Algorithms for Mining the Concise and Lossless Representation of High Utility Itemsets
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 117 Clickmyproject
An Efficient Projection Based Indexing Approach For Mining High Utility Itemsets
 
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Recently, utility mining has widely been discussed in the field of data mining. It finds high utility item sets by considering both profits and quantities of items in transactional data sets. However, most of the existing approaches are based on the principle of level wise processing, as in the traditional two-phase utility mining algorithm to find a high utility item sets. In this paper, we propose an efficient utility mining approach that adopts an indexing mechanism to speed up the execution and reduce the memory requirement in the mining process. The indexing mechanism can imitate the traditional projection algorithms to achieve the aim of projecting sub-databases for mining. In addition, a pruning strategy is also applied to reduce the number of unpromising item sets in mining. Finally, the experimental results on synthetic data sets and on a real data set show the superior performance of the proposed approach.
Final Year Projects | Efficient Algorithms for Mining High Utility Itemsets from Transactional
 
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Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-778-1155 +91 958-553-3547 +91 967-774-8277 Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected] chat: http://support.elysiumtechnologies.com/support/livechat/chat.php
Views: 810 MyProjectBazaar
USpan: an efficient algorithm for mining high utility sequential patterns (KDD 2012)
 
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USpan: an efficient algorithm for mining high utility sequential patterns KDD 2012 Junfu Yin Zhigang Zheng Longbing Cao Sequential pattern mining plays an important role in many applications, such as bioinformatics and consumer behavior analysis. However, the classic frequency-based framework often leads to many patterns being identified, most of which are not informative enough for business decision-making. In frequent pattern mining, a recent effort has been to incorporate utility into the pattern selection framework, so that high utility (frequent or infrequent) patterns are mined which address typical business concerns such as dollar value associated with each pattern. In this paper, we incorporate utility into sequential pattern mining, and a generic framework for high utility sequence mining is defined. An efficient algorithm, USpan, is presented to mine for high utility sequential patterns. In USpan, we introduce the lexicographic quantitative sequence tree to extract the complete set of high utility sequences and design concatenation mechanisms for calculating the utility of a node and its children with two effective pruning strategies. Substantial experiments on both synthetic and real datasets show that USpan efficiently identifies high utility sequences from large scale data with very low minimum utility.
Efficient Vertical Mining of High Average Utility Itemsets- IEEE PROJECTS 2018
 
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Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases
 
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Views: 154 Ecway Karur
Selective Database Projections Based Approach for Mining High Utility Itemsets- IEEE PROJECTS 2018
 
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Selective Database Projections Based Approach for Mining High Utility Itemsets- IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project, IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS, ,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS, IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS, IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,IEEE PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS,FINAL YEAR PROJECTS
Frequent Itemsets Mining with Differential Privacy over Large-scale Data
 
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Frequent Itemsets Mining with Differential Privacy over Large-scale Data S/W: JAVA, JSP, MYSQL IEEE 2018-19
Frequent Itemsets Mining With Differential Privacy Over Large-Scale Data
 
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Frequent Itemsets Mining With Differential Privacy Over Large-Scale Data To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, #37, Kamaraj Salai,Thattanchavady, Puducherry -9. Mobile: (0)9952649690, Email: [email protected], Website: https://www.jpinfotech.org Frequent itemsets mining with differential privacy refers to the problem of mining all frequent itemsets whose supports are above a given threshold in a given transactional dataset, with the constraint that the mined results should not break the privacy of any single transaction. Current solutions for this problem cannot well balance efficiency, privacy, and data utility over large-scale data. Toward this end, we propose an efficient, differential private frequent itemsets mining algorithm over large-scale data. Based on the ideas of sampling and transaction truncation using length constraints, our algorithm reduces the computation intensity, reduces mining sensitivity, and thus improves data utility given a fixed privacy budget. Experimental results show that our algorithm achieves better performance than prior approaches on multiple datasets.
Views: 65 jpinfotechprojects
Final Year Projects | Efficient Mining of Freqent Itemsets on large uncertain databases
 
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Final Year Projects | Efficient Mining of Freqent Itemsets on large uncertain databases More Details: Visit http://clickmyproject.com/a-secure-erasure-codebased-cloud-storage-system-with-secure-data-forwarding-p-128.html Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 247 Clickmyproject
Machine Learning #81 Frequent Itemset Mining
 
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Machine Learning #81 Frequent Itemset Mining In this lecture of machine learning we are going to see frequent itemset mining. In frequent itemset mining tutorial we will see some examples of frequent itemset mining algorithm. Frequent itemset mining is a branch of data mining works by looking at sequences of events or action, for example the order in which a normal human being get dressed. Usually Shirt first? Pants first? Socks may be the second item or second shirt if its winter? In frequent itemset mining, the base data takes the form of sets of transactions that each has a number of items. Machine Learning Complete Tutorial/Lectures/Course from IIT (nptel) @ https://goo.gl/AurRXm Discrete Mathematics for Computer Science @ https://goo.gl/YJnA4B (IIT Lectures for GATE) Best Programming Courses @ https://goo.gl/MVVDXR Operating Systems Lecture/Tutorials from IIT @ https://goo.gl/GMr3if MATLAB Tutorials @ https://goo.gl/EiPgCF
Views: 1010 Xoviabcs
Efficient Algorithms for Mining the Concise and Lossless Representation of High Utility Itemsets
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://myprojectbazaar.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/myprojectbazaar Mail Us: [email protected]
Views: 26 MyProjectBazaar
Efficient Algorithms for Mining the Concise and Lossless Representation of High Utility Itemsets
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://myprojectbazaar.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/myprojectbazaar Mail Us: [email protected]
Views: 59 MyProjectBazaar
Advance Mining of Temporal High Utility Itemset
 
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Advance Mining of Temporal High Utility Itemset
A New Methodology for Mining Frequent Itemsets on Temporal Data
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/clickmyproject Mail Us: [email protected]
Views: 116 Clickmyproject
Advance Mining Of Temporal High Utility Itemset
 
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Views: 96 siva6351
evaluation of predictive data mining algorithms in soil data classification for- IEEE PROJECTS 2018
 
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evaluation of predictive data mining algorithms in soil data classification for optimized crop recom- IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project NETWORK AND SERVICE MANAGEMENT 1. Bacterial foraging optimization based Radial Basis Function Neural Network (BRBFNN) for identification and classification of plant leaf diseases: An automatic approach towards Plant Pathology(12 February 2018 ) 2. Fault-Tolerant Clustering Topology Evolution Mechanism of Wireless Sensor Networks (08 June 2018) SOFTWARE ENGINEERING 1. Reviving Sequential Program Birthmarking for Multithreaded Software Plagiarism Detection 2. EVA: Visual Analytics to Identify Fraudulent Events DATA MINING 1. Opinion Aspect Relations in Cognizing Customer Feelings via Reviews(24 January 2018) 2. Optimizing a multi-product continuous-review inventory model with uncertain demand, quality improvement, setup cost reduction, and variation control in lead time (27 June 2018) 3. Evaluation of Predictive Data Mining Algorithms in Soil Data Classification for Optimized Crop Recommendation (09 April 2018) 4. Prediction of Effective Rainfall and Crop Water Needs using Data Mining Techniques (01 February 2018) 5. A Secure Client-Side Framework for Protecting the Privacy of Health DataStored on the Cloud( 04 June 2018) 6. Greedy Optimization for K-Means-Based Consensus Clustering(April 2018) 7. A Two-stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings 8. Principal Component Analysis Based Filtering for Scalable, High Precision k-NN Search 9. Entity Linking: A Problem to Extract Corresponding Entity with Knowledge Base 10. Collective List-Only Entity Linking: A Graph-Based Approach 11. Web Media and Stock Markets : A Survey and Future Directionsfrom a Big Data Perspective 12. Selective Database Projections Based Approach for Mining High-Utility Itemsets 13. Reverse k Nearest Neighbor Search over Trajectories 14. Range-based Nearest Neighbor Queries with Complex-shaped Obstacles 15. Predicting Contextual Informativeness for Vocabulary Learning 16. Online Product Quantization 17. Highlighter: automatic highlighting of electronic learning documents 18. Fuzzy Bag-of-Words Model for Document Representation 19. Frequent Itemsets Mining with Differential Privacy over Large-scale Data 20. Fast Cosine Similarity Search in Binary Space with Angular Multi-index Hashing 21. Efficient Vertical Mining of High Average-Utility Itemsets based on Novel Upper-Bounds 22. Document Summarization for Answering Non-Factoid Queries 23. Discovering Canonical Correlations between Topical andTopological Information in Document Networks 24. Complementary Aspect-based Opinion Mining 25. An Efficient Method for High Quality and Cohesive Topical Phrase Mining 26. A Weighted Frequent Itemset Mining Algorithm for Intelligent Decision in Smart Systems 27. A Correlation-based Feature Weighting Filter for Naive Bayes 28. Comments Mining With TF-IDF: The Inherent Bias and Its Removal 29. Bayesian Nonparametric Learning for Hierarchical and Sparse Topics 30. Supervised Topic Modeling using Hierarchical Dirichlet Process-based Inverse Regression: Experiments on E-Commerce Applications
Optimizing a multi product continuous review inventory model with uncertain - IEEE PROJECTS 2018
 
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Optimizing a multi product continuous review inventory model with uncertain demand,quality improveme- IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project NETWORK AND SERVICE MANAGEMENT 1. Bacterial foraging optimization based Radial Basis Function Neural Network (BRBFNN) for identification and classification of plant leaf diseases: An automatic approach towards Plant Pathology(12 February 2018 ) 2. Fault-Tolerant Clustering Topology Evolution Mechanism of Wireless Sensor Networks (08 June 2018) SOFTWARE ENGINEERING 1. Reviving Sequential Program Birthmarking for Multithreaded Software Plagiarism Detection 2. EVA: Visual Analytics to Identify Fraudulent Events DATA MINING 1. Opinion Aspect Relations in Cognizing Customer Feelings via Reviews(24 January 2018) 2. Optimizing a multi-product continuous-review inventory model with uncertain demand, quality improvement, setup cost reduction, and variation control in lead time (27 June 2018) 3. Evaluation of Predictive Data Mining Algorithms in Soil Data Classification for Optimized Crop Recommendation (09 April 2018) 4. Prediction of Effective Rainfall and Crop Water Needs using Data Mining Techniques (01 February 2018) 5. A Secure Client-Side Framework for Protecting the Privacy of Health DataStored on the Cloud( 04 June 2018) 6. Greedy Optimization for K-Means-Based Consensus Clustering(April 2018) 7. A Two-stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings 8. Principal Component Analysis Based Filtering for Scalable, High Precision k-NN Search 9. Entity Linking: A Problem to Extract Corresponding Entity with Knowledge Base 10. Collective List-Only Entity Linking: A Graph-Based Approach 11. Web Media and Stock Markets : A Survey and Future Directionsfrom a Big Data Perspective 12. Selective Database Projections Based Approach for Mining High-Utility Itemsets 13. Reverse k Nearest Neighbor Search over Trajectories 14. Range-based Nearest Neighbor Queries with Complex-shaped Obstacles 15. Predicting Contextual Informativeness for Vocabulary Learning 16. Online Product Quantization 17. Highlighter: automatic highlighting of electronic learning documents 18. Fuzzy Bag-of-Words Model for Document Representation 19. Frequent Itemsets Mining with Differential Privacy over Large-scale Data 20. Fast Cosine Similarity Search in Binary Space with Angular Multi-index Hashing 21. Efficient Vertical Mining of High Average-Utility Itemsets based on Novel Upper-Bounds 22. Document Summarization for Answering Non-Factoid Queries 23. Discovering Canonical Correlations between Topical andTopological Information in Document Networks 24. Complementary Aspect-based Opinion Mining 25. An Efficient Method for High Quality and Cohesive Topical Phrase Mining 26. A Weighted Frequent Itemset Mining Algorithm for Intelligent Decision in Smart Systems 27. A Correlation-based Feature Weighting Filter for Naive Bayes 28. Comments Mining With TF-IDF: The Inherent Bias and Its Removal 29. Bayesian Nonparametric Learning for Hierarchical and Sparse Topics 30. Supervised Topic Modeling using Hierarchical Dirichlet Process-based Inverse Regression: Experiments on E-Commerce Applications
Weighted frequent itemset mining algorithml
 
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Weighted frequent item set mining algorithm S/W: JAVA, JSP, MYSQL
A frequent itemsets mining algorithm based on matrix in sliding window over data streams
 
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