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Utility Mining Algorithm for High Utility Item sets from Transactional Databases

Arati W Borkar
2014 IOSR Journal of Computer Engineering  
in low memory based systems for mining high utility itemsets from large transactional datasets and hence needs to address further as well.  ...  The discovery of item sets with high utility like profits is referred by mining high utility item sets from a transactional database.  ...  Singh sir to contributed this paper and Fellow for their valuable comments and sharing their knowledge.  ... 
doi:10.9790/0661-16253440 fatcat:jgo3k7cfnndhjnk5an3yxan224

Survey on Algorithms for High Utility Itemset Generation

Prof Jyoti B. Kulkarni, Aishwarya Dingre, Sonal Bhosale, Deepali Mehroliya, Shivani Mudgal
2017 IJARCCE  
We hereby present the study of issues related to the different structures used and algorithms for mining the high utility itemsets.  ...  Efficient discovery of the frequent and useful itemsets in huge datasets is a crucial task in data mining. In the recent years, many methods have been proposed for generating high utility patterns.  ...  Kulkarni for her invaluable guidance and supervision that helped us in our research. She has always encouraged us to explore new concepts and pursue newer research problems.  ... 
doi:10.17148/ijarcce.2017.6322 fatcat:az2sdhonebcwlbzr66f3zqulhq

A review and analysis on knowledge discovery and data mining techniques

Bhagawan Singh, Vivek Dubey
2018 International Journal of Advanced Technology and Engineering Exploration  
The FP-development calculation is quicker than the Apriori algorithm around a request of extent, the recursive FPgrowth calculation for mining incessant itemsets needs to over and over build restrictive  ...  example bases and contingent example tree during Review Article Abstract Data mining is used for the knowledge discovery in the area of engineering, medical diagnosis, business analytics, etc.  ...  They have analyzed on the high utility infrequent itemsets using utility pattern rare itemset (UPRI) algorithm.  ... 
doi:10.19101/ijatee.2018.541006 fatcat:xctz44fa75hotj7dpagsxpomsy

Mining high utility itemsets without candidate generation

Mengchi Liu, Junfeng Qu
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
HUI-Miner uses a novel structure, called utility-list, to store both the utility information about an itemset and the heuristic information for pruning the search space of HUI-Miner.  ...  High utility itemsets refer to the sets of items with high utility like profit in a database, and efficient mining of high utility itemsets plays a crucial role in many reallife applications and is an  ...  Using the utility-list structure, the HUI-Miner algorithm can mine high utility itemsets without candidate generation.  ... 
doi:10.1145/2396761.2396773 dblp:conf/cikm/LiuQ12 fatcat:mzkmn63q5jhunpbuvx5elymvxq

A Survey of Utility-Oriented Pattern Mining

Wensheng Gan, Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent Tseng, Philip Yu
2019 IEEE Transactions on Knowledge and Data Engineering  
The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications to derive beneficial knowledge.  ...  A comprehensive review of advanced topics of existing high-utility pattern mining techniques is offered, with a discussion of their pros and cons.  ...  Since the usefulness of association rule [9] can be defined as a utility function based on the business objective, the utility and confidence can be used to extend the concepts of high-utility itemset  ... 
doi:10.1109/tkde.2019.2942594 fatcat:nipxkmyfb5cyxh2662xbz6feo4

A Survey of Utility-Oriented Pattern Mining [article]

Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent S. Tseng, Philip S. Yu
2019 arXiv   pre-print
The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications to derive beneficial knowledge.  ...  A comprehensive review of advanced topics of existing high-utility pattern mining techniques is offered, with a discussion of their pros and cons.  ...  Acknowledgment We would like to thank the editors and anonymous reviewers for their detailed comments and constructive suggestions which have improved the quality of this paper.  ... 
arXiv:1805.10511v2 fatcat:gfv2uvkq2vhyrcinpvteqn37su

An Efficient Data Structure for Fast Mining High Utility Itemsets [article]

Zhi-Hong Deng, Shulei Ma, He Liu
2015 arXiv   pre-print
Based on PUN-lists, we present a method, called MIP (Mining high utility Itemset using PUN-Lists), for fast mining high utility itemsets. The efficiency of MIP is achieved with three techniques.  ...  In this paper, we propose a novel data structure called PUN-list, which maintains both the utility information about an itemset and utility upper bound for facilitating the processing of mining high utility  ...  Table 6 shows the time consumption for mining high utility 2-itemsets and all high utility itemsets when HUI-Miner and MIP_twu run on dataset chain with minimum utility = 0.005%.  ... 
arXiv:1510.02188v1 fatcat:mda2fwcjm5fszhrdit7joonkf4

A Survey on High Utility Rare Itemset Mining

Zhang Wenbo, Shenyang Ligong University, Kanika Middha, Jeetesh Kumar Jain, SRCEM, SRCEM
2015 International Journal of Smart Business and Technology  
Rare itemsets have been explained that are used for the mining of the items having utility value less than the threshold but are of great use.  ...  In this paper, a survey about basic data mining and its related fields like association rule mining has been undertaken.  ...  In this paper, an algorithm, FHURI (Fuzzy High Utility Rare Itemset Mining) is presented to efficiently and effectively mine very-high (and high) utility rare itemsets from databases, by fuzzification  ... 
doi:10.21742/ijsbt.2015.3.1.05 fatcat:aryouacqiba4hf47zy6zlhiad4

A Survey on Mining Frequent Itemsets over Data Streams

Shailvi Maurya, Sneha Ambhore, Sneha Parit
2017 International Journal of Computer Applications  
Mining frequent itemsets over data stream has been challenging task.  ...  The incoming data from various sources like ecommerce website, click streams, text, audio, weather forecasting etc. are massive unbounded and high speed that it is impractical to store all, process and  ...  itemsets quickly which utilized the structural properties of frequent itemsets for fast discovery.  ... 
doi:10.5120/ijca2017916030 fatcat:ojkfobsynnedhhp7d7ayxabo7a

Proof Learning in PVS with Utility Pattern Mining

M. Saqib Nawaz, Philippe Fournier-Viger, Ji Zhang
2020 IEEE Access  
Experimental results suggest that combining frequent pattern mining techniques, such as sequential pattern mining and high utility itemset mining, with proof assistants, such as PVS, is useful to learn  ...  INDEX TERMS Frequent patterns, high utility itemset mining, proof steps, proof sequences, PVS.  ...  He is also the Founder of the popular SPMF open-source data mining library, which provides more than 170 algorithms for identifying various types of patterns in data.  ... 
doi:10.1109/access.2020.3004199 fatcat:l5lly5fmrjbwdi2jurwfogci6y

Mining top-k high utility patterns over data streams

Morteza Zihayat, Aijun An
2014 Information Sciences  
The method is based on a compressed tree structure, called HUDS-tree, that can be used to efficiently find potential top-k high utility itemsets over sliding windows.  ...  less than the minimum utility threshold (called high TWU itemsets) and then compute the exact utilities of high TWU itemsets to identify those whose utility satisfies the minimum utility threshold.  ...  Thus, unlike in frequent itemset mining, we cannot use the utility of an itemset to prune the search space in high utility itemset mining because a superset of a low utility itemset may be a high utility  ... 
doi:10.1016/j.ins.2014.01.045 fatcat:xhdukofadzhfpmyoryisx6uu2q

Using Tree Structure to Mine High Temporal Fuzzy Utility Itemsets

Tzung-Pei Hong, Cheng-Yu Lin, Wei-Ming Huang, Shu-Min Li, Shyue-Liang Wang, Jerry Chun-Wei Lin
2020 IEEE Access  
Other related methods [23] [30] used by this model were proposed to find high utility itemsets. Several variants of mining high utility itemsets were also proposed.  ...  They extended the Apriori algorithm and used the fuzzy concept to mine interesting linguistic patterns [12] .  ... 
doi:10.1109/access.2020.3018155 fatcat:lzt3hj2a5vborjti7ishaed7ae

Frequent Pattern Retrieval on Data Streams by using Sliding Window

P. Kumar, P. Rao
2021 EAI Endorsed Transactions on Energy Web  
In different applications like recommender frameworks and market examination, regular patterns play a significant role in useful mining data.  ...  In this examination, the sliding window is utilized to build the framework and FP tree applied to mine the dataset's valuable data.  ...  Frequent Pattern Mining (FPM) provides useful information, and studies have been carried out, such as mining high utility patterns [4] , [5] , [6] .  ... 
doi:10.4108/eai.13-1-2021.168091 fatcat:ud3pbbgmq5gl3b525spburyl7i

Extracting the Frequent Item Sets by Using Greedy Strategy in Hadoop

Mr. B. Veerendranadh, Mr.M. Naveen Kumar
2017 IOSR Journal of Computer Engineering  
The adjusted calculation presents elements time devoured in exchanges filtering for competitor itemsets and the quantities of tenets produced are additionally diminished.  ...  As it were, every one of the information on the planet are of no incentive without components to proficiently and successfully remove data and learning from them.  ...  They extend the proposed calculation to mine continuous itemsets in the MLMS structure [6] .  ... 
doi:10.9790/0661-1904018390 fatcat:cxgz4xhubva4va6bqrjv6422zq

SVM-based association rules for knowledge discovery and classification

Ali Anaissi, Madhu Goyal
2015 2015 2nd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE)  
This paper delivers a strategy for the implementation of a systematic analysis framework built on the established principles used in data mining and machine learning.  ...  We employ Apriori algorithm and support vector machine to implement our recommendation systems.  ...  METHODS This paper delivers a strategy for the implementation of a systematic analysis framework built on the established principles used in data mining and machine learning.  ... 
doi:10.1109/apwccse.2015.7476236 fatcat:z6ejnnhuvvgklaac63jztf7lyu
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