Contents & References of Creating a recommender system on the web using user profiles and machine learning methods
List:
List of Figures D
List of Tables E
Chapter One: General Research. 2
1-1- Statement of the problem. 3
1-2- Necessity of research. 4
1-3- Research objectives. 5
1-4- Research structure. 5
The second chapter: Literature of the subject. 7
2-1- Definition of words and terms. 8
2-2- Web challenges. 9
2-3- Types of web mining methods. 10
2-3-1- Application-based web mining. 11
2-3-2- content-based web mining 14
2-3-3- structure-based web mining. 15
2-4- Web personalization. 16
2-4-1- The benefits of the web personalization system. 20
2-4-2- Law-based filtering systems. 20
2-4-3- Content-based filtering systems 20
2-4-4- Collaborative filtering systems. 21
2-5- Recommender systems. 21
2-6- Web personalization based on application-based web mining. 22
2-7- Data sources 24
2-7-1- Application data. 24
2-7-2- Content data 25
2-7-3- Structure data. 25
2-8- Clustering. 26
2-8-1- K-Means algorithm. 27
2-8-2- Similarity criteria. 28
2-9- Neural networks. 30
Chapter Three: Previous works. 32
3-1- Approaches based on exploring association rules and clustering. 33
3-2- Combined methods in web personalization. 38
3-3- Approaches based on indexing and keywords. 42
3-4- An overview of web recommender systems. 43
3-4-1- Web recommender system. 43
3-4-2- Proposal production methods. 44
3-4-2-1- methods based on collaborative filter. 44
3-4-2-2- Content-based methods 44
3-4-2-3- Knowledge-based methods. 45
3-4-2-4- Combined recommender systems. 46
3-4-3- Comparison of proposal generation methods. 46
Chapter Four: Suggested method. 49
4-1- Data pre-processing 51
4-1-1- Data cleaning 51
4-1-2- Identification and reconstruction of user visit sessions. 52
4-2- Creating a profile for personalization on the web. 52
4-2-1- Creation of the sitting vector. 52
4-2-2- Clearing sessions 54
4-2-3- Creating user profiles. 55
4-3- Clustering profiles based on user behavior. 55
4-4- Building recommender system using neural networks. 56
Chapter five: Implementation and evaluation of the proposed method. 58
5-1- Pre-processing stage and construction of meeting vectors. 59
5-2- Clustering stage. 61
3-5- The stage of generating suggestions using neural network. 62
5-4- Evaluation of the proposed system. 63
Sixth chapter: conclusion and future suggestions. 66
6-1- Results of research and analysis 67
6-2- Future works. 68
List of references. 70
Source:
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