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One of the Natural Language Processing (NLP) studies that has been widely researched is automatic text summarization. There are a lot of techniques and methods that are proposed for text summarization. However, not much attention have been given on the coherence and cohesion in text. The aim of this study to present an idea to combine Sequential Pattern Mining (SPM) as text representation extracting algorithm and Deep Learning (DL) which is a powerful machine learning technique widely used recently in various data mining studies. This study uses descriptive research methodology that collects all of the facts and information which are related to SPM and DL for text summarization, where NLP as the body of knowledge, SPM and DL as the method, and text summarization as the domain problem that need to be solved. The findings of the study are presented as a logical framework diagram. The illustration of the logical framework can be implemented to further improve automatic text summarization results, in particular, to improve its coherence and cohesion.