Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Discovering Patterns from Large and Dynamic Sequential Data
Journal of Intelligent Information Systems
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficient enumeration of frequent sequences
Proceedings of the seventh international conference on Information and knowledge management
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Online Generation of Association Rules
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Sequence mining in categorical domains: incorporating constraints
Proceedings of the ninth international conference on Information and knowledge management
Shared State for Distributed Interactive Data Mining Applications
Distributed and Parallel Databases - Special issue: Parallel and distributed data mining
Data Mining for Measuring and Improving the Success of Web Sites
Data Mining and Knowledge Discovery
Efficiently Mining Approximate Models of Associations in Evolving Databases
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Interactive Constraint-Based Sequential Pattern Mining
ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
Fast Discovery of Sequential Patterns by Memory Indexing
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
FFS - An I/O-Efficient Algorithm for Mining Frequent Sequences
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Efficient Algorithms for Incremental Update of Frequent Sequences
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Incremental mining of sequential patterns in large databases
Data & Knowledge Engineering
Towards NIC-based intrusion detection
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Go Green: Recycle and Reuse Frequent Patterns
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Information Systems - Databases: Creation, management and utilization
IncSpan: incremental mining of sequential patterns in large database
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
FS-Miner: efficient and incremental mining of frequent sequence patterns in web logs
Proceedings of the 6th annual ACM international workshop on Web information and data management
Incremental personalized web page mining utilizing self-organizing HCMAC neural network
Web Intelligence and Agent Systems
Interactive sequence discovery by incremental mining
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
A Services Oriented Framework for Next Generation Data Analysis Centers
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
Efficient Algorithms for Mining and Incremental Update of Maximal Frequent Sequences
Data Mining and Knowledge Discovery
Extended Real-Time Learning Behavior Mining
ICALT '05 Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies
Efficient mining method for retrieving sequential patterns over online data streams
Journal of Information Science
A framework for representing navigational patterns as full temporal objects
ACM SIGecom Exchanges
Research issues in data stream association rule mining
ACM SIGMOD Record
A fuzzy data mining algorithm for incremental mining of quantitative sequential patterns
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
On progressive sequential pattern mining
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Computational aspects of mining maximal frequent patterns
Theoretical Computer Science
Incremental and interactive mining of web traversal patterns
Information Sciences: an International Journal
An incremental data mining algorithm for discovering web access patterns
International Journal of Business Intelligence and Data Mining
Intelligent Data Analysis - Knowlegde Discovery from Data Streams
RETRACTED: Efficient mining of temporal emerging itemsets from data streams
Expert Systems with Applications: An International Journal
Efficient algorithms for incremental maintenance of closed sequential patterns in large databases
Data & Knowledge Engineering
A decremental algorithm of frequent itemset maintenance for mining updated databases
Expert Systems with Applications: An International Journal
When to update the sequential patterns of stream data?
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Incremental mining of sequential patterns using prefix tree
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
IMCS: incremental mining of closed sequential patterns
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
A taxonomy of sequential pattern mining algorithms
ACM Computing Surveys (CSUR)
Incorporating terminology evolution for query translation in text retrieval with association rules
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Interval-orientation patterns in spatio-temporal databases
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
Efficient algorithms for finding frequent substructures from semi-structured data streams
JSAI'03/JSAI04 Proceedings of the 2003 and 2004 international conference on New frontiers in artificial intelligence
SITAC: discovering semantically identical temporally altering concepts in text archives
Proceedings of the 14th International Conference on Extending Database Technology
Efficient incremental mining of frequent sequence generators
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
A novel mining algorithm for periodic clustering sequential patterns
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
A decremental algorithm for maintaining frequent itemsets in dynamic databases
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Improvements of incspan: incremental mining of sequential patterns in large database
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Sequential pattern mining -- approaches and algorithms
ACM Computing Surveys (CSUR)
User Behaviour Pattern Mining from Weblog
International Journal of Data Warehousing and Mining
PLASMA-HD: probing the lattice structure and makeup of high-dimensional data
Proceedings of the VLDB Endowment
Techniques for data-driven curriculum analysis
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Incremental mining of sequential patterns: Progress and challenges
Intelligent Data Analysis
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The discovery of frequent sequences in temporal databases is an important data mining problem. Most current work assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. In this paper, we propose novel techniques for maintaining sequences in the presence of a) database updates, and b) user interaction (e.g. modifying mining parameters). This is a very challenging task, since such updates can invalidate existing sequences or introduce new ones. In both the above scenarios, we avoid re-executing the algorithm on the entire dataset, thereby reducing execution time. Experimental results confirm that our approach results in execution time improvements of up to several orders of magnitude in practice.