Quality of experience (QoE) estimation of Web services via text mining tools

General Information:

Cover Page:

Outline:

1 General Introduction
1.1 Context & Problematic
1.2 Manuscript plan
2 Introduction to The Web Services
2.1 Introduction
2.2 Web Services
2.3 Web Services Key words
2.4 Web Services Framework
2.5 Web services Architecture
2.6 Work-Flow Web services
2.7 Problems of Current Web Services
2.8 Strength
2.9 Weakness
2.10 Web Services Reputation
2.10.1 Quality of service (QoS)
2.11 Conclusion
3 Introduction to Text Mining
3.1 Introduction
3.2 Text Mining
3.3 Text Mining Process
3.3.1 Text Preprocessing
3.3.2 Text Transformation
3.3.3 Text Mining Methods
3.4 Text Mining Techniques
3.4.1 Information Retrieval
3.4.2 Information Extraction
3.4.3 Categorization
3.4.4 Clustering
3.4.5 Visualization
3.4.6 Summarization
3.5 Comparison Text Mining Technique
3.6 Application of Text Mining
3.6.1 Classification of Scientific Documents
3.6.2 Security
3.6.3 Business Intelligence
3.6.4 Other point
3.7 Advantage and Disadvantage in Text Mining
3.7.1 Advantages of Text Mining
3.7.2 Disadvantages of Text Mining
3.8 Conclusion
4 Reputation Assessment
4.1 Introduction
4.2 Used directory and evaluation metrics
4.2.1 Programmable Web
4.2.2 G2Crowd
4.2.3 Evaluation metrics
4.3 Modelization
4.4 Assessment Process / Experimental Evaluation
4.4.1 Prepossessing of Data
4.4.2 Feature Extraction
4.4.3 Subjectivity Analysis
4.5 Sentimental Analysis
4.6 Reputation Assessment
4.7 Results
4.8 Conclusion
5 General Conclusion
Bibliography

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