ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
TSP: Mining Top-K Closed Sequential Patterns
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Approximating a collection of frequent sets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
TSP: Mining top-k closed sequential patterns
Knowledge and Information Systems
Summarizing itemset patterns: a profile-based approach
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Fast Algorithms for Frequent Itemset Mining Using FP-Trees
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Spatio-Temporal Sequential Patterns
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Summarization — Compressing Data into an Informative Representation
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Generating semantic annotations for frequent patterns with context analysis
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting redundancy-aware top-k patterns
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing itemset patterns using probabilistic models
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
LinkClus: efficient clustering via heterogeneous semantic links
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Matrix apriori: speeding up the search for frequent patterns
DBA'06 Proceedings of the 24th IASTED international conference on Database and applications
Mining compressed commodity workflows from massive RFID data sets
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Mining top-k strongly correlated item pairs without minimum correlation threshold
International Journal of Knowledge-based and Intelligent Engineering Systems
Frequent Closed Sequence Mining without Candidate Maintenance
IEEE Transactions on Knowledge and Data Engineering
The minimum consistent subset cover problem and its applications in data mining
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarization – compressing data into an informative representation
Knowledge and Information Systems
Semantic annotation of frequent patterns
ACM Transactions on Knowledge Discovery from Data (TKDD)
An efficient algorithm for mining closed inter-transaction itemsets
Data & Knowledge Engineering
A data mining proxy approach for efficient frequent itemset mining
The VLDB Journal — The International Journal on Very Large Data Bases
Extracting k most important groups from data efficiently
Data & Knowledge Engineering
Effective and efficient itemset pattern summarization: regression-based approaches
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Top-k Data Sources Ranking for Query on Deep Web
WISE '08 Proceedings of the 9th international conference on Web Information Systems Engineering
A new concise representation of frequent itemsets using generators and a positive border
Knowledge and Information Systems
On effective presentation of graph patterns: a structural representative approach
Proceedings of the 17th ACM conference on Information and knowledge management
Blind paraunitary equalization
Signal Processing
Expert Systems with Applications: An International Journal
Implicit Groups of Web Pages as Constrained Top N Concepts
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Non-redundant sequential rules-Theory and algorithm
Information Systems
Cartesian contour: a concise representation for a collection of frequent sets
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A Bipartite Graph Framework for Summarizing High-Dimensional Binary, Categorical and Numeric Data
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Mining closed patterns in multi-sequence time-series databases
Data & Knowledge Engineering
Robust and distributed top-n frequent-pattern mining with SAP BW accelerator
Proceedings of the VLDB Endowment
Ontological support for Association Rule Mining
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Summary queries for frequent itemsets mining
Journal of Systems and Software
International Journal of Intelligent Information and Database Systems
Block interaction: a generative summarization scheme for frequent patterns
Proceedings of the ACM SIGKDD Workshop on Useful Patterns
Transactions on rough sets XII
ESTATE: strategy for exploring labeled spatial datasets using association analysis
DS'10 Proceedings of the 13th international conference on Discovery science
An efficient algorithm for mining erasable itemsets
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
A novel evolutionary method to search interesting association rules by keywords
Expert Systems with Applications: An International Journal
Mining top-k regular-frequent itemsets using database partitioning and support estimation
Expert Systems with Applications: An International Journal
Fast mining erasable itemsets using NC_sets
Expert Systems with Applications: An International Journal
An efficient approach for mining top-k fault-tolerant repeating patterns
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Summarizing frequent patterns using profiles
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
K-optimal pattern discovery: an efficient and effective approach to exploratory data mining
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
COBRA: closed sequential pattern mining using bi-phase reduction approach
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
ExMiner: an efficient algorithm for mining top-k frequent patterns
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Comment spam detection by sequence mining
Proceedings of the fifth ACM international conference on Web search and data mining
Efficient mining of association rules based on formal concept analysis
Formal Concept Analysis
A framework for mining association rules
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Mining the k-most interesting frequent patterns sequentially
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Efficient mining top-k regular-frequent itemset using compressed tidsets
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Searching interesting association rules based on evolutionary computation
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Mining top-K high utility itemsets
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Recent frequent itemsets mining over data streams
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Graph classification: a diversified discriminative feature selection approach
Proceedings of the 21st ACM international conference on Information and knowledge management
Adaptive Study Design Through Semantic Association Rule Analysis
International Journal of Software Science and Computational Intelligence
Mining high coherent association rules with consideration of support measure
Expert Systems with Applications: An International Journal
Anytime algorithms for mining groups with maximum coverage
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Fast mining Top-Rank-k frequent patterns by using Node-lists
Expert Systems with Applications: An International Journal
Mining top-k frequent patterns over data streams sliding window
Journal of Intelligent Information Systems
| Hi-index | 0.01 |
In this paper, we propose a new mining task: mining top-kfrequent closed patterns of length no less than min_l, wherek is the desired number of frequent closed patterns to bemined, and min _l is the minimal length of each pattern.An efficient algorithm, called TFP, is developed for mining such patterns without minimum support. Two methods, closed_node_count and descendant_sum are proposedto effiectively raise support threshold and prune FP-tree bothduring and after the construction of FP-tree. During themining process, a novel top-down and bottom-up combinedFP-tree mining strategy is developed to speed-up support-raising and closed frequent pattern discovering. In addition,a fast hash-based closed pattern verification scheme has beenemployed to check efficiently if a potential closed pattern isreally closed.Our performance study shows that in most cases, TFPoutperforms CLOSET and CHARM, two efficient frequentclosed pattern mining algorithms, even when both are running with the best tuned min_support. Furthermore, themethod can be extended to generate association rules andto incorporate user-specified constraints. Thus we concludethat for frequent pattern mining, mining top-k frequent closedpatterns without min support is more preferable than thetraditional min_support-based mining.