Text Mining: Classification, Clustering, and Summarization
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".
Deadline for manuscript submissions: closed (15 April 2019) | Viewed by 5104
Special Issue Editor
Special Issue Information
Dear Colleagues,
Text mining is defined as the process of extract implicit knowledge from textual data, as a special type of data mining. Main instances of text mining are text classification, text clustering, text summarization, and text segmentation. The text classification means the process of classifying a text into one among predefined categories; especially, spam mail filtering is the typical instance of text categorization. Text clustering means the process of segmenting a group of texts into subgroups each of which contains content based similar texts. Recently, as well as machine learning algorithms, such as K Nearest Neighbour, Naïve Bayes, and Support Vector Machine, deep learning algorithms are applied to the text classification.
The Special Issue on “Text Mining: Classification, Clustering, and Summarization” aims to improve the performances of each text mining tasks by applying deep learning algorithms, to derive hybrid tasks by combing the text mining tasks with each other, and to apply the text mining tasks to the real problems such as fraud document detection and financial prediction. Authors should submit papers describing significant, original and unpublished work. Possible topics include, but are not limited to:
- Machine Learning Algorithms to improve Text Mining Tasks
- Application of Deep Learning Algorithms to Text Mining Tasks
- Application of Text Mining System to Real Tasks
- Hybrid Text Mining Tasks
- Web Mining: Web Contents Mining, Web Structure Mining, and Web Usage Mining
- Multimedia Mining: Hybrid Mining of Multimedia Data
Prof. Dr. Duke Taeho Jo
Guest Editor
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Keywords
- Word Classification
- Word Clustering
- Automatic Keyword Extraction
- Index Optimization
- Text Classification
- Text Clustering
- Text Summarization
- Text Segmentation
- Machine Learning
- Deep Learning
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