Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Sequence mining in categorical domains: incorporating constraints
Proceedings of the ninth international conference on Information and knowledge management
Data mining: concepts and techniques
Data mining: concepts and techniques
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth
ICDE '01 Proceedings of the 17th International Conference on Data Engineering
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Generalization of pattern-growth methods for sequential pattern mining with gap constraints
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Mining Sequential Patterns with Negative Conclusions
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Effect of Preprocessing on Extractive Summarization with Maximal Frequent Sequences
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Using lexical patterns for extracting hyponyms from the web
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Terms derived from frequent sequences for extractive text summarization
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Authorship attribution using word sequences
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
A text mining approach for definition question answering
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Using machine learning and text mining in question answering
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
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Sequential pattern mining is an important tool for solving many data mining tasks and it has broad applications. However, only few efforts have been made to extract this kind of patterns in a textual database. Due to its broad applications in text mining problems, finding these textual patterns is important because they can be extracted from text independently of the language. Also, they are human readable patterns or descriptors of the text, which do not lose the sequential order of the words in the document. But the problem of discovering sequential patterns in a database of documents presents special characteristics which make it intractable for most of the apriori-like candidate-generation-and-test approaches. Recent studies indicate that the pattern-growth methodology could speed up the sequential pattern mining. In this paper we propose a pattern-growth based algorithm (DIMASP) to discover all the maximal sequential patterns in a document database. Furthermore, DIMASP is incremental and independent of the support threshold. Finally, we compare the performance of DIMASP against GSP, DELISP, GenPrefixSpan and cSPADE algorithms.