Web Mining in Social Media: use cases, business value, and algorithmic approaches for corporate intelligence
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
[Köln]
Social Media Verl.
2011
|
| Schriftenreihe: | Social Web
3 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | 152 S. graph. Darst. 2100 mm x 1480 mm |
| ISBN: | 9783941835078 |
Internformat
MARC
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| 100 | 1 | |a Graubner-Müller, Alexander |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Web Mining in Social Media |b use cases, business value, and algorithmic approaches for corporate intelligence |c Alexander Graubner-Müller |
| 264 | 1 | |a [Köln] |b Social Media Verl. |c 2011 | |
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Datensatz im Suchindex
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| adam_text | IMAGE 1
TABLE OF CONTENT
1. INTRODUCTION 10
1.1. PROBLEM OUTLINE 10
1.2. OBJECTIVES OF RESEARCH 12
1.3. METHODOLOGY AND STRUCTURE 13
2. CORPORATE INTELLIGENCE AND THE INTERNET 17 2.1. CORPORATE INFORMATION
DEMAND IN THE 21 SL CENTURY 17
2.2. RATIONALES BEHIND TAPPING THE INTERNET AS INFORMATION SOURCE 21
2.2.1. THE INTERNET IS A TREMENDOUS BODY OF DATA 22 2.2.2. THE INTERNET
IS OMNIPRESENT AND TRULY GLOBAL 24 2.2.3. THE INTERNET LEVERAGES
INFORMATION 25
2.2.4. THE INTERNET IS SOCIAL AND INTERACTIVE 26 2.2.5. THE INTERNET
FOSTERS A CULTURE OF COLLABORATION 27
3. WEB MINING FUNDAMENTALS 31
3.1. DEFINITION AND TAXONOMY OF WEB MINING 31 3.1.1. WEB STRUCTURE
MINING 33
3.1.2. WEB USAGE MINING 34
3.1.3. WEB CONTENT MINING 34
3.2. ENABLING TECHNOLOGIES AND RELATED DISCIPLINES 35 3.2.1. DATA MINING
AND KNOWLEDGE DISCOVERY IN DATA BASES 37
3.2.2. INFORMATION RETRIEVAL AND WEB SEARCH 40
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1010013130
DIGITALISIERT DURCH
IMAGE 2
3.2.3. NATURAL LANGUAGE PROCESSING AND
AUTOMATED INFORMATION EXTRACTION 44
3.3. CHARACTERISTICS OF WEB DOCUMENTS 47
3.3.1. WEB TECHNOLOGIES 48
3.3.2. CHARACTERISTICS OF WEB DOCUMENTS 51
3.3.3. ACCESSIBILITY 53
3.4. SYNTHESIS: WEB MINING AND ITS CONTEXTS 56
4. DIMENSIONS OF A WEB MINING SCENARIO 57
4.1. MODEL APPLICATION SCENARIOS FOR BUSINESS PURPOSES .57 4.1.1.
RESEARCH AND DEVELOPMENT 59
4.1.1.1. TECHNOLOGY INTELLIGENCE 59
4.1.1.2. TREND SCOUTING 60
4.1.1.3. CONSUMER BEHAVIOR ANALYSIS 60
4.1.2. MARKETING AND SALES 62
4.1.2.1. PRODUCT AND BRAND IMAGE ANALYSIS 62 4.1.2.2. CAMPAIGN
EVALUATION 63
4.1.2.3. COMMUNITY AND OPINION LEADER DETECTION 63
4.1.3. DISTRIBUTION 64
4.1.3.1. SITE AND LOCATION PLANNING 64
4.1.4. CUSTOMER SERVICE 65
4.1.4.1. PRODUCT RECOMMENDATION 65
4.1.4.2. CUSTOMER FEEDBACK ANALYSIS 66
IMAGE 3
4.1.5. PROCUREMENT 67
4.1.5.1. CONTENT ACQUISITION 67
4.1.5.2. SUPPLIER AND PRICE MONITORING 67
4.1.6. RISK AND PUBLIC RELATION MANAGEMENT 68
4.1.6.1. MEDIA INTELLIGENCE 68
4.1.6.2. INVESTOR SENTIMENT ANALYSIS 69
4.1.6.3. FRAUD DETECTION 70
4.1.7. STRATEGIC MANAGEMENT 70
4.1.7.1. COMPETITIVE AND STAKEHOLDER INTELLIGENCE 71
4.1.8. HUMAN RESOURCE MANAGEMENT 72
4.1.8.1. LABOR MARKET INTELLIGENCE 72
4.1.8.2. EMPLOYER REPUTATION 72
4.2. CONCEPTUAL DIMENSIONS OF A WEB MINING SCENARIO..73
4.2.1. RESEARCH OBJECTIVES 74
4.2.1.1. EXTRACTION 75
4.2.1.2. IDENTIFICATION 76
4.2.1.3. EXPLORATION 78
4.2.1.4. INTERPRETATION 79
4.2.2. ADDITIONAL DIMENSIONS 81
4.2.2.1. SOURCES 81
4.2.2.2. GRANULARITY 83
4.2.2.3. MINING INTERVAL 84
4.2.2.4. LEVEL OF AGGREGATION 85
IMAGE 4
4.3. FUNCTIONAL AND TECHNICAL ASPECTS OF A
WEB MINING SCENARIO 86
4.3.1. RESOURCE FINDING AND RETRIEVING 87
4.3.1.1. WEB CRAWLING 88
4.3.1.2. AUTOMATED INTERFACE SUBMISSION 91
4.3.1.3. API INTEGRATION 92
4.3.2. INFORMATION SELECTION AND PREPROCESSING 93 4.3.2.1. DOCUMENT
PREPROCESSING 93
4.3.2.2. STRUCTURED DATA EXTRACTION 95
4.3.2.3. DATA CLEANING AND TRANSFORMATION 97 4.3.2.4. NATURAL LANGUAGE
TEXT PREPROCESSING 98
4.3.3. PATTERN ANALYSIS AND RECOGNITION 100
4.3.3.1. QUERY OPERATIONS 101
4.3.3.2. TEXT CLASSIFICATION METHODS 102
4.3.3.3. TEXT PATTERN ANALYSIS 104
4.3.3.4. STATISTICAL METHODS 107
4.3.4. EVALUATION AND REVIEW 108
4.3.5. REPORTING AND CONSOLIDATION 110
4.3.5.1. SUMMARIZATION I LL
4.3.5.2. VISUALIZATION I LL
4.3.5.3. DEPLOYMENT 112
4.4. SYNTHESIS: ORCHESTRATING A WEB MINING SCENARIO ...113
IMAGE 5
5. PRACTICAL CONSIDERATIONS OF WEB MINING:
A CASE STUDY ....115
5.1. INFOSPEED: COMPANY AND BUSINESS MODEL 116
5.2. INFOSPEED: TECHNOLOGIES AND PROCESSES. 121
5.2.1. RESOURCE FINDING AND RETRIEVING 122
5.2.2. INFORMATION SELECTION AND PREPROCESSING 123 5.2.3. PATTERN
ANALYSIS AND RECOGNITION 126
5.2.4. REPORTING AND EVALUATION 130
5.3. INFOSPEED: BUSINESS VALUE OF WEB KNOWLEDGE 131
5.4. EVALUATION... 135
6. CONCLUSION 139
LIST OF FIGURES 145
BIBLIOGRAPHY .146
INTERVIEW LIST 152
|
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| author | Graubner-Müller, Alexander |
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| dewey-tens | 650 - Management and auxiliary services |
| discipline | Informatik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV037324885 |
| illustrated | Illustrated |
| indexdate | 2024-08-01T10:53:35Z |
| institution | BVB |
| isbn | 9783941835078 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-022478983 |
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| physical | 152 S. graph. Darst. 2100 mm x 1480 mm |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Social Media Verl. |
| record_format | marc |
| series | Social Web |
| series2 | Social Web |
| spellingShingle | Graubner-Müller, Alexander Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence Social Web Web-Intelligent-System (DE-588)7601884-2 gnd World Wide Web 2.0 (DE-588)7548364-6 gnd Business Intelligence (DE-588)4588307-5 gnd Unternehmen (DE-588)4061963-1 gnd Data Mining (DE-588)4428654-5 gnd Wissensextraktion (DE-588)4546354-2 gnd |
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| title | Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence |
| title_auth | Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence |
| title_exact_search | Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence |
| title_full | Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence Alexander Graubner-Müller |
| title_fullStr | Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence Alexander Graubner-Müller |
| title_full_unstemmed | Web Mining in Social Media use cases, business value, and algorithmic approaches for corporate intelligence Alexander Graubner-Müller |
| title_short | Web Mining in Social Media |
| title_sort | web mining in social media use cases business value and algorithmic approaches for corporate intelligence |
| title_sub | use cases, business value, and algorithmic approaches for corporate intelligence |
| topic | Web-Intelligent-System (DE-588)7601884-2 gnd World Wide Web 2.0 (DE-588)7548364-6 gnd Business Intelligence (DE-588)4588307-5 gnd Unternehmen (DE-588)4061963-1 gnd Data Mining (DE-588)4428654-5 gnd Wissensextraktion (DE-588)4546354-2 gnd |
| topic_facet | Web-Intelligent-System World Wide Web 2.0 Business Intelligence Unternehmen Data Mining Wissensextraktion |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022478983&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV037310961 |
| work_keys_str_mv | AT graubnermulleralexander webmininginsocialmediausecasesbusinessvalueandalgorithmicapproachesforcorporateintelligence |
Inhaltsverzeichnis
THWS Würzburg Zentralbibliothek Lesesaal
| Signatur: |
1000 ST 205 G774 1000 ST 205 G774st |
|---|---|
| Exemplar 1 | ausleihbar Verfügbar Bestellen |
| Exemplar 2 | ausleihbar Verfügbar Bestellen |
THWS Würzburg Teilbibliothek SHL, Raum I.2.11
| Signatur: |
1340 ST 205 G774st |
|---|---|
| Exemplar 1 | nicht ausleihbar Verfügbar Bestellen |