Finding maximal sequential patterns in text document collections and single documents
In this paper, two algorithms for discovering all the Maximal Sequential Patterns (MSP) in a document collection and in a single document are presented. The proposed algorithms follow the “pattern-growth strategy” where small frequent sequences are found first with the goal of growing them to obtain...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Estado: | Versión aceptada para publicación |
| Data de publicação: | 2010 |
| País: | México |
| Recursos: | Instituto Nacional de Astrofísica, Óptica y Electrónica |
| Repositório: | Repositorio Institucional del INAOE |
| Idioma: | inglês |
| OAI Identifier: | oai:inaoe.repositorioinstitucional.mx:1009/1403 |
| Acesso em linha: | http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1403 |
| Access Level: | Acceso aberto |
| Palavra-chave: | info:eu-repo/classification/Text mining/Text mining info:eu-repo/classification/Maximal sequential patterns/Maximal sequential patterns info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/12 info:eu-repo/classification/cti/1203 |
| Resumo: | In this paper, two algorithms for discovering all the Maximal Sequential Patterns (MSP) in a document collection and in a single document are presented. The proposed algorithms follow the “pattern-growth strategy” where small frequent sequences are found first with the goal of growing them to obtain MSP. Our algorithms process the documents in an incremental way avoiding re-computing all the MSP when new documents are added. Experiments showing the performance of our algorithms and comparing against GSP, DELISP, GenPrefixSpan and cSPADE algorithms over public standard databases are also presented. |
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