發(fā)布時(shí)間：2021-08-12 11:29

　　Living in the information age,today’s people mostly spend their time with gadgets to do（almost）everything,like dealing with the online transactions,updating social media status,commenting one’s status or company’s products,sharing pictures and videos,applying jobs via web based job search engines,etc.These phenomena make data hence also information are continuously being produced,streamed and received in a big volume and high velocity by（almost）every digital devices and censors over the entire g... 

【文章來源】：上海交通大學(xué)上海市 211工程院校 985工程院校 教育部直屬院校

【文章頁數(shù)】：189 頁

【學(xué)位級別】：博士

【文章目錄】：
ABSTRACT
CHAPTER 1. INTRODUCTION
    1.1 RESEARCH BACKGROUND
    1.2 PROBLEMS OF STATE-OF-ART APPROACHES
        1.2.1 Job Dataset Clustering Problem
        1.2.2 The Static Skillset Generation
        1.2.3 The Mining Emerging Skillsets in Long Term Period Problem
    1.3 THE PROPOSED SOLUTIONS
        1.3.1 Frequent Contextual Termsets based Job Dataset Clustering
        1.3.2 Skillsets' Gap Discovery based on Incremental FP Mining
        1.3.3 Mining Emerging Skillsets in Dynamic Data using Fibonacci Windows Model
        1.3.4 Push-Front TTWM and Push-Front Fibonacci Windows Model
    1.4 MY WORKS’PORTRAIT
    1.5 DISSERTATION STRUCTURE
CHAPTER 2. RELATED WORKS
    2.1 FREQUENT PATTERNS BASIC CONCEPT
        2.1.1 Mining the Frequent Patterns
        2.1.2 Methods for Mining the Frequent Patterns
        2.1.3 Classes of Frequent Patterns
    2.2 MINING FPs OVER DATA STREAM
        2.2.1 Landmark Windows Model
        2.2.2 Damped Windows Model
        2.2.3 Sliding Windows Model
        2.2.4 Tilted-Time Windows Model
    2.3 EMERGING PATTERNS CONCEPT
        2.3.1 Basic Concept
        2.3.2 Mining Emerging Patterns in Dynamic Data
CHAPTER 3. FREQUENT PATTERNS BASED DOCUMENTS CLUSTERING
    3.1 INTRODUCTION
        3.1.1 Background
        3.1.2 Distance based Clustering Methods
        3.1.3 Frequent Patterns based Clustering Methods
        3.1.4 Problems of Existing Methods
    3.2 THE PROPOSED SOLUTIONS
        3.2.1 The Proposed Framework
        3.2.2 Mining out the Frequent Contextual Termsets
        3.2.3 Text Clustering using FCTs
    3.3 EXPERIMENTAL WORKS,RESULTS AND DISCUSSIONS
        3.3.1 Experimental Works No. 1
        3.3.2 Results and Discussions
        3.3.3 Experimental Works No. 2
        3.3.4 Results and Discussions
    3.4 SUMMARY
CHAPTER 4. FREQUENT PATTERNS BASED SKILLSET'S GAP DISCOVERY
    4.1 INTRODUCTION
        4.1.1 Background
        4.1.2 Existing Methods to Minimize Skillset' Gap
        4.1.3 Problems of Existing Methods
    4.2 THE PROPOSED SOLUTIONS
        4.2.1 Glossary of Skills and Dataset of Jobs and Students
        4.2.2 Frequent Skillsets
        4.2.3 Skill Coverage and Probability of Student to Get a Job
        4.2.4 Skillsets-Students Visualizing Matrix
    4.3 EXPERIMENTAL WORKS,RESULTS AND DISCUSSIONS
        4.3.1 Experiment Settings
        4.3.2 Results and Discussions
    4.4 SUMMARY
CHAPTER 5. FIBONACCI WINDOWS MODEL
    5.1 INTRODUCTION
        5.1.1 Background
        5.1.2 Problems of State-Of-Art's Data Windows Models
    5.2 THE PROPOSED FIBONACCI WINDOWS MODEL
        5.2.2 Definitions
        5.2.3 Fibonacci Windows' Element Updating Mechanism
    5.3 FINDING EPs IN DATA STREAM USING FIBONACCI WINDOWS
    5.4 EXPERIMENTAL WORKS,RESULTS AND DISCUSSIONS
        5.4.1 The Experiment Framework
        5.4.2 Experimental Works No. 1
        5.4.3 Experimental Works No. 2
        5.4.4 Experimental Works No. 3
    5.5 SUMMARY
CHAPTER 6. PUSH-FRONT TILTED-TIME WINDOWS BASED MODEL
    6.1 INTRODUCTION
        6.1.1 Background
        6.1.2 Problems of the Traditional Model
    6.2 THE PROPOSED PUSH-FRONT TILTED-TIME WINDOWS BASED MODEL
        6.2.1 Basic Approach
        6.2.2 The Push-Front Fibonacci Windows Model
    6.3 EXPERIMENTAL WORKS,RESULTS AND DISCUSSIONS
        6.3.1 The Experiment Framework
        6.3.2 Experimental Works No. 1
        6.3.3 Experimental Works No. 2
        6.3.4 Experimental Works No. 3
    6.4 RELIABILITY ANALYSIS
    6.5 SUMMARY
CHAPTER 7. GENERAL SUMMARIES AND FUTURE WORKS
    7.1 GENERAL SUMMARIES
    7.2 FUTURE WORKS
REFERENCES
符號與標(biāo)記
公式推導(dǎo)
THE PUBLISHED PAPERS
攻讀博士學(xué)位期間參與的科研項(xiàng)目
ACKNOWLEDGEMENT



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