Recommender systems for the social web:
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin ; Heidelberg
Springer
2012
|
| Schriftenreihe: | Intelligent systems reference library
32 |
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XIX, 222 S. graph. Darst. 24 cm |
| ISBN: | 9783642256936 9783642256943 |
Internformat
MARC
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| 100 | 1 | |a Pazos Arias, José J. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Recommender systems for the social web |c José J. Pazos Arias, Ana Fernández Vilas, and Rebeca P. Díaz Redondo |
| 264 | 1 | |a Berlin ; Heidelberg |b Springer |c 2012 | |
| 300 | |a XIX, 222 S. |b graph. Darst. |c 24 cm | ||
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| 490 | 1 | |a Intelligent systems reference library |v 32 | |
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| 700 | 1 | |a Fernández Vilas, Ana |e Verfasser |4 aut | |
| 700 | 1 | |a Díaz Redondo, Rebeca P. |e Verfasser |4 aut | |
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Datensatz im Suchindex
| _version_ | 1805146188838600704 |
|---|---|
| adam_text |
IMAGE 1
CONTENTS
PART I: GENERAL ASPECTS 1 SOCIAL RECOMMENDER SYSTEMS 3
GEORG GROH, STEFAN BIRNKAMMERER, AND VALERIA KOLLHOFER 1.1 INTRODUCTION
3
1.2 RELATED WORK ON RECOMMENDER SYSTEMS 5
1.2.1 CONTENT-BASED FILTERING 5
1.2.2 COLLABORATIVE FILTERING 6
1.2.3 OTHER APPROACHES 7
1.3 SOCIAL RECOMMENDER SYSTEMS 8
1.3.1 WHAT: ITEM-BASED, HOW: SOCIAL 9
1.3.2 WHAT: SOCIAL, HOW: SOCIAL 10
1.3.3 WHAT: SOCIAL, HOW: ITEM-BASED 11
1.3.4 TEAM RECOMMENDATION 12
1.3.5 RECOMMENDATIONS FOR GROUPS 13
1.4 COLLABORATIVE FILTERING VS. SOCIAL FILTERING: TASTE RELATED DOMAINS
14
1.5 COLLABORATIVE FILTERING VS. SOCIAL FILTERING FOR DISCUSSION BOARDS
19
1.5.1 EMPIRICAL STUDY 21
1.5.1.1 EXPERIMENT ONE 25
1.5.1.2 EXPERIMENT TWO 3 0
1.5.1.3 COMPARISON O F RESULTS TO RELATED STUDIES . . . 36
1.5.2 FUTURE PROSPECTS 36
1.6 CONCLUSION AND FUTURE WORK 38
REFERENCES 38
2 LEGAL ASPECTS O F RECOMMENDER SYSTEMS IN THE WEB 2.0: TRUST, LIABILITY
AND SOCIAL NETWORKING 43
TERESA RODRIGUEZ DE LAS HERAS BALLELL 2.1 PERSONALIZATION AND
RECOMMENDATION IN THE SOCIAL WEB: GENERATING TRUST 44
HTTP://D-NB.INFO/101684414X
IMAGE 2
XII
CONTENTS
2.2 UNDERSTANDING SOCIAL NETWORKING CHALLENGES 4 6
2.2.1 SOCIAL NETWORKING AND NEW PRIVACY EXPECTATIONS 47
2.2.2 RISKS, LIABILITY AND PRIVACY-ENHANCING STRATEGIES FOR SOCIAL
NETWORKS 48
2.2.3 THE ROLE OF CONSENT AND THE BUILDING O F OUR DIGITAL EGO 51
2.3 INFORMATION, OPINIONS AND RECOMMENDATIONS: THE ADDED-VALUE OF
RECOMMENDER SYSTEMS 52
2.3.1 SPOTTING LEGAL CONCERNS O F RECOMMENDER SYSTEMS . . . . 5 4 2.4
ACHIEVING A BALANCE BETWEEN PRIVACY AND PERSONALIZATION IN RECOMMENDER
SYSTEMS: GENERATING TRUST AND ENFORCING LIABILITY RULES 6 0
REFERENCES 61
PART II: INTEROPERABILITY FOR RECOMMENDATION
3 CHALLENGES IN TAG RECOMMENDATIONS FOR COLLABORATIVE TAGGING SYSTEMS 65
ROBERT JASCHKE, ANDREAS HOTHO, FOLKE MITZLAFF, AND GERD STUMME 3.1
INTRODUCTION 6 6
3.2 FOUNDATIONS AND STATE OF THE ART 67
3.2.1 TAG RECOMMENDATION PROBLEM 67
3.2.2 TAG RECOMMENDATION TASKS 68
3.2.3 STATE O F THE ART 68
3.3 EVALUATION 6 9
3.3.1 MEASURES 69
3.3.2 DATASETS 69
3.3.3 BASELINES 7 0
3.4 CONTENT-BASED TAG RECOMMENDATIONS 71
3.4.1 DATASETS 7 1
3.4.2 APPROACHES 7 2
3.4.2.1 OVERVIEW 72
3.4.2.2 PREPROCESSING 73
3.4.2.3 DATA SELECTION/SOURCES 7 3
3.4.2.4 PERSONALIZATION 7 4
3.4.2.5 RANKING/SCORING 7 4
3.4.3 RESULTS AND DISCUSSION 75
3.4.3.1 DISCOVERY CHALLENGE 2008 75
3.4.3.2 DISCOVERY CHALLENGE 2009 7 6
3.4.3.3 COMPARISON O F THE DISCOVERY CHALLENGE 2008 WITH THE DISCOVERY
CHALLENGE 2009 ON THE COMPLETE DATASET 76
3.4.4 LESSONS LEARNT 77
3.5 GRAPH-BASED TAG RECOMMENDATIONS 77
3.5.1 DATASETS 77
IMAGE 3
CONTENTS XIII
3.5.2 APPROACHES 78
3.5.3 RESULTS AND DISCUSSION 79
3.5.4 LESSONS LEARNT 7 9
3.6 ONLINE TAG RECOMMENDATIONS 80
3.6.1 SETTING 80
3.6.2 APPROACHES 80
3.6.3 RESULTS AND DISCUSSION 81
3.6.4 LESSONS LEARNT 82
3.7 SUMMARY AND FUTURE CHALLENGES 82
REFERENCES 85
4 A MULTI-CRITERIA APPROACH FOR AUTOMATIC ONTOLOGY RECOMMENDATION USING
COLLECTIVE KNOWLEDGE 89
MARCOS MARTINEZ-ROMERO, JOSE M. VAZQUEZ-NAYA, JAVIER PEREIRA, AND
ALEJANDRO PAZOS 4.1 INTRODUCTION 89
4.2 RELATED WORK 9 0
4.3 AN APPROACH FOR AUTOMATIC ONTOLOGY RECOMMENDATION 91
4.3.1 SEMANTIC EXPANSION AND ONTOLOGY RETRIEVAL 91
4.3.2 ONTOLOGY EVALUATION 92
4.3.2.1 CONTEXT COVERAGE EVALUATION 93
4.3.2.2 SEMANTIC RICHNESS EVALUATION 94
4.3.2.3 POPULARITY EVALUATION 98
4.3.3 NORMALIZATION 9 9
4.3.4 FINAL ONTOLOGY SCORE 100
4.4 EVALUATION AND RESULTS 100
4.5 CONCLUSIONS AND FUTURE WORK 102
REFERENCES 103
PART III: TRUST & RECOMMENDATION
5 IMPLICIT TRUST NETWORKS: A SEMANTIC APPROACH TO IMPROVE COLLABORATIVE
RECOMMENDATIONS 107
MANUELA I. MARTIN-VICENTE, ALBERTO GIL-SOLLA, AND MANUEL RAMOS-CABRER
5.1 INTRODUCTION 107
5.2 RELATED WORK 110
5.3 IMPLICIT TRUST-AWARE NEIGHBORHOOD SELECTION I L L
5.3.1 A SEMANTIC METHOD FOR MINING TRUST RELATIONS 112
5.3.2 BUILDING AN IMPLICIT TRUST NETWORK 114
5.3.3 OUR REPUTATION MEASURE 116
5.3.4 INCORPORATING TRUST AND REPUTATION IN THE NEIGHBORHOOD FORMATION
117
5.4 LESSONS LEARNED 118
REFERENCES 118
IMAGE 4
XIV CONTENTS
6 SOCIAL RECOMMENDATION BASED ON A RICH AGGREGATION MODEL 121
IDO GUY 6.1 INTRODUCTION 121
6.2 SOCIAL AGREGATION MODEL 122
6.3 PEOPLE RECOMMENDATION 123
6.3.1 RECOMMENDING FAMILIAR PEOPLE 123
6.3.2 RECOMMENDING STRANGERS 126
6.4 CONTENT RECOMMENDATION 129
6.4.1 RECOMMENDATION BASED ON SOCIAL RELATIONSHIPS 129
6.4.2 RECOMMENDING BASED ON TAGS 132
6.5 CONCLUSION AND FUTURE WORK 134
REFERENCES 135
PART IV: GROUP RECOMMENDATION
7 GROUP RECOMMENDER SYSTEMS: NEW PERSPECTIVES IN THE SOCIAL WEB 139
IVAN CANTADOR AND PABLO CASTELLS 7.1 INTRODUCTION 139
7.2 SOCIAL CHOICE THEORY 141
7.3 GROUP RECOMMENDER SYSTEMS 148
7.3.1 GROUP RECOMMENDATION BASED ON MODEL AGGREGATION 149
7.3.2 GROUP RECOMMENDATION BASED ON PREDICTION AGGREGATION 150
7.3.3 GROUP FORMATION 151
7.3.4 COOPERATIVE CONSENSUS 152
7.4 OPEN RESEARCH PROBLEMS IN GROUP RECOMMENDER SYSTEMS 152 7.5 GROUP
RECOMMENDER SYSTEMS FOR THE SOCIAL WEB 153
7.6 CONCLUSIONS 155
REFERENCES 155
8 AUGMENTING COLLABORATIVE RECOMMENDERS BY FUSING SOCIAL RELATIONSHIPS:
MEMBERSHIP AND FRIENDSHIP 159
QUAN YUAN, LI CHEN, AND SHIWAN ZHAO 8.1 INTRODUCTION 159
8.2 RELATED WORK 161
8.2.1 FUSION O F SOCIAL RELATIONSHIPS 161
8.2.2 GRAPH-BASED RECOMMENDER ALGORITHM 162
8.3 FUSING SOCIAL RELATIONSHIPS INTO RECOMMENDERS 163
8.3.1 FUSING VIA GRAPH 163
8.3.1.1 GRAPH CONSTRUCTION FOR SOCIAL COMMUNITY . . 164 8.3.1.2 FUSION O
F SOCIAL DATA BY ADJUSTING WEIGHTS O F EDGES 165
8.3.1.3 PERSONALIZED RANDOM WALK ON SOCIAL GRAPH 166
IMAGE 5
CONTENTS X V
8.3.2 COMPLEXITY ANALYSIS 167
8.4 EXPERIMENTS 167
8.4.1 DATASETS 167
8.4.2 EVALUATION METRICS 168
8.4.3 RESULTS 169
8.4.3.1 RESULTS ON SPARSE DATASET 169
8.4.3.2 RESULTS ON DENSE DATASET 171
8.4.3.3 OVERALL ACCURACY COMPARISON 172
8.5 CONCLUSION AND FUTURE WORK 173
REFERENCES 173
PARTV: APPLICATIONS
9 RECOMMENDATIONS ON THE MOVE 179
ALICIA RODRIGUEZ-CARRION, CELESTE CAMPO, AND CARLOS GARCIA-RUBIO 9.1
INTRODUCTION 179
9.2 PREDICTING FUTURE LOCATIONS IN MOBILE PHONES 180
9.2.1 LOCATION DATA SOURCES 180
9.2.2 LOCATION PREDICTORS 182
9.2.2.1 LZ ALGORITHM 183
9.2.2.2 LEZI UPDATE ALGORITHM 184
9.2.2.3 ACTIVE LEZI ALGORITHM 186
9.2.3 PERFORMANCE RESULTS 187
9.3 IMPROVING RECOMMENDER PREDICTIONS 188
9.3.1 IMPLANTING "FALSE MEMORIES" 188
9.3.2 GOING SOCIAL 188
9.4 PROTOTYPE IMPLEMENTATION 190
9.5 CONCLUSIONS 191
REFERENCES 192
10 SCORM AND SOCIAL RECOMMENDATION: A WEB 2.0 APPROACH TO E-LEARNING 195
REBECA P. DIAZ REDONDO, ANA FERNANDEZ VILAS, JOSE J. PAZOS ARIAS,
ALBERTO GIL SOLLA, MANUEL RAMOS CABRER, AND JORGE GARCIA DUQUE 10.1
INTRODUCTION 195
10.2 SCORM SHIFTS TO WEB 2.0 196
10.2.1 BRIEF SCORM OVERVIEW 196
10.2.2 ARCHITECTONIC SHIFT: DRIVING SCORM TO THE WOA 197 10.2.3 SOCIAL
SHIFT: COLLABORATIVE SCORM 198
10.3 EDUCATECA OVERVIEW 199
10.4 COLLABORATIVE SUPPORT TO RECOMMENDATION 201
10.4.1 MODELING LEARNING SERVICES AS PERCEIVED BY TAGGING USERS 202
10.4.2 MODELING LEARNERS 202
10.4.3 SIMPLE COMMPARISON O F TAG CLOUDS 203
IMAGE 6
X V I
CONTENTS
10.4.4 SEMANTICALLY-ENHANCED COMARISON O F TAG CLOUDS 203
10.4.5 HYBRID COLLABORATIVE FILTERING SCHEME 205
10.5 CONCLUSIONS 205
REFERENCES 206
PART VI: CONCLUSIONS AND OPEN TRENDS
11 CONCLUSIONES AND OPEN TRENDS 211
JOSE J. PAZOS ARIAS, ANA FERNANDEZ VILAS, AND REBECA P. DIAZ REDONDO
11.1 INTRODUCTION 211
11.2 SOCIAL AGGREGATION MODEL: GROUPS AND TRUST IN THE NETWORK . . . .
213 11.3 RECONCILING COLLABORATIVE TAGGING WITH SEMANTIC REASONING . . .
215 11.4 RECOMMENDING IN THE CLOUD 217
REFERENCES 219 |
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| series | Intelligent systems reference library |
| series2 | Intelligent systems reference library |
| spelling | Pazos Arias, José J. Verfasser aut Recommender systems for the social web José J. Pazos Arias, Ana Fernández Vilas, and Rebeca P. Díaz Redondo Berlin ; Heidelberg Springer 2012 XIX, 222 S. graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Intelligent systems reference library 32 Literaturangaben World Wide Web 2.0 (DE-588)7548364-6 gnd rswk-swf Empfehlungssystem (DE-588)7511891-9 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content World Wide Web 2.0 (DE-588)7548364-6 s Empfehlungssystem (DE-588)7511891-9 s DE-604 Fernández Vilas, Ana Verfasser aut Díaz Redondo, Rebeca P. Verfasser aut Erscheint auch als Online-Ausgabe Recommender Systems for the Social Web Intelligent systems reference library 32 (DE-604)BV035704685 32 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3905475&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024777521&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pazos Arias, José J. Fernández Vilas, Ana Díaz Redondo, Rebeca P. Recommender systems for the social web Intelligent systems reference library World Wide Web 2.0 (DE-588)7548364-6 gnd Empfehlungssystem (DE-588)7511891-9 gnd |
| subject_GND | (DE-588)7548364-6 (DE-588)7511891-9 (DE-588)4143413-4 |
| title | Recommender systems for the social web |
| title_auth | Recommender systems for the social web |
| title_exact_search | Recommender systems for the social web |
| title_full | Recommender systems for the social web José J. Pazos Arias, Ana Fernández Vilas, and Rebeca P. Díaz Redondo |
| title_fullStr | Recommender systems for the social web José J. Pazos Arias, Ana Fernández Vilas, and Rebeca P. Díaz Redondo |
| title_full_unstemmed | Recommender systems for the social web José J. Pazos Arias, Ana Fernández Vilas, and Rebeca P. Díaz Redondo |
| title_short | Recommender systems for the social web |
| title_sort | recommender systems for the social web |
| topic | World Wide Web 2.0 (DE-588)7548364-6 gnd Empfehlungssystem (DE-588)7511891-9 gnd |
| topic_facet | World Wide Web 2.0 Empfehlungssystem Aufsatzsammlung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3905475&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024777521&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035704685 |
| work_keys_str_mv | AT pazosariasjosej recommendersystemsforthesocialweb AT fernandezvilasana recommendersystemsforthesocialweb AT diazredondorebecap recommendersystemsforthesocialweb |