Recommender systems and the social web: leveraging tagging data for recommender systems
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Wiesbaden
Springer Vieweg
2013
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
| Beschreibung: | 112 S. graph. Darst. |
| ISBN: | 9783658019471 9783658019488 3658019476 |
| DOI: | 10.1007/978-3-658-01948-8 |
Internformat
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| 245 | 1 | 0 | |a Recommender systems and the social web |b leveraging tagging data for recommender systems |c Fatih Gedikli |
| 264 | 1 | |a Wiesbaden |b Springer Vieweg |c 2013 | |
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Datensatz im Suchindex
| _version_ | 1804150306166013952 |
|---|---|
| adam_text | Contents
Introduction
1
1.1 Motivation ............................................ 1
1.2
Concept
of rating items by rating tags
............................. 2
1.3
Contributions
........................................... 3
1.4
Overview of the dissertation
................................... 4
1.5
Publications
............................................ 4
Preliminaries
7
2.1
Basic recommendation techniques
................................ 7
2.1.1
Notation and symbols
.................................. 7
2.1.2
Collaborative filtering
.................................. 8
2.1.3
Content-based recommendations
............................ 12
2.2
Evaluating recommender systems
................................ 15
2.2.1
Offline experiments
.................................... 16
2.2.2
User studies
........................................ 18
2.2.3
Online experiments
.................................... 20
2.3
Recommendations based on Social Web tagging data
..................... 21
2.3.1
Using tags as content
.................................. 22
2.3.2
Clustering approaches
.................................. 24
2.3.3
Hybrid approaches
.................................... 26
2.3.4
Tag-enhanced recommenders
.............................. 29
2.3.5
Tag-based explanations
................................. 31
2.3.6
Outlook
.......................................... 32
LocalRank
—
A graph-based tag recommender
33
3.1
Introduction
............................................ 33
3.2
Tag recommendations
...................................... 34
3.3
LocalRank
............................................. 36
3.4
Evaluation
............................................. 38
3.4.1
Data sets
......................................... 38
3.4.2
Evaluation procedure
.................................. 38
3.4.3
Accuracy results
..................................... 39
3.4.4
Run-time efficiency results
................................ 40
3.5
Summary and outlook
...................................... 42
Improving recommendation accuracy based on item-specific tag preferences
43
4.1
Introduction
............................................ 43
4.2
Illustrative example and overview of the approach
...................... 44
4.3
Estimating unknown tag preferences
.............................. 45
4.4
Predicting item ratings from tag preferences
.......................... 46
4.5
Evaluation
............................................. 47
4.5.1
Data sets, tag quality, and data preprocessing
..................... 48
4.5.2
Algorithms
........................................ 49
4.5.3
Accuracy metrics
..................................... 50
4.5.4
Results and discussion
.................................. 51
4.6
Related work and discussion
................................... 53
4.7
Summary and outlook
...................................... 54
5
Evaluation of explanation interfaces in the form of tag clouds
57
5.1
Introduction
............................................ 57
5.2
Evaluation factors of explanations in recommender systems
................. 58
5.3
Overview of the evaluated explanation interfaces
....................... 60
5.4
Experimental setup
........................................ 62
5.4.1
Experimental procedure
................................. 62
5.4.2
Participants of the study
................................ 64
5.4.3
Data collected in the experiment
............................ 65
5.5
Hypotheses, results, and discussion
............................... 65
5.5.1
Efficiency
......................................... 66
5.5.2
Satisfaction
........................................ 66
5.5.3
Effectiveness and persuasiveness
............................ 66
5.5.4
Implications for trust
.................................. 67
5.6
Summary
............................................. 67
6
An analysis of the effects of using different explanation styles
69
6.1
Introduction
............................................ 69
6.2
Overview of the evaluated explanation interfaces
....................... 70
6.2.1
Herlocker
et al. s
explanation methods
......................... 71
6.2.2
Tag cloud based explanation interfaces
......................... 72
6.3
Experimental setup
........................................ 74
6.3.1
Experimental procedure
................................. 74
6.3.2
The underlying tagged movie data set
......................... 76
6.3.3
Hypothesis development
................................. 76
6.3.4
Participants of the study
................................ 77
6.3.5
Data collected in the experiment
............................ 77
6.4
Results and discussion
...................................... 78
6.4.1
Efficiency
......................................... 79
6.4.2
Effectiveness and persuasiveness
............................ 79
6.4.3
Transparency
....................................... 82
6.4.4
Satisfaction
........................................ 83
6.4.5
Relationships between variables
............................. 84
6.4.6
Implications for trust
.................................. 86
6.5
Summary
............................................. 87
7
Summary and perspectives
89
7.1
Contributions and limitations
.................................. 89
7.2
Perspectives
............................................ 91
A Joint publications
93
8
Additional material for Chapter
6 95
B.I Explanation interfaces used in the study
............................ 95
B.I.I Bar charts
......................................... 95
B.1.2 Rating- and prediction-based explanations
....................... 95
B.2 Statistics
............................................. 97
B.2.1 Standard deviations
................................... 97
B.2.
2
Friedman test
....................................... 97
B.2.3 Wilcoxon Signed-Rank test
............................... 98
|
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| discipline | Informatik Wirtschaftswissenschaften |
| doi_str_mv | 10.1007/978-3-658-01948-8 |
| format | Thesis Book |
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| genre_facet | Hochschulschrift |
| id | DE-604.BV040985320 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T00:36:49Z |
| institution | BVB |
| isbn | 9783658019471 9783658019488 3658019476 |
| language | English |
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| spelling | Gedikli, Fatih Verfasser (DE-588)13803141X aut Recommender systems and the social web leveraging tagging data for recommender systems Fatih Gedikli Wiesbaden Springer Vieweg 2013 112 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Zugl.: Dortmund, Techn. Univ., Diss., 2012 Empfehlungssystem (DE-588)7511891-9 gnd rswk-swf Social Tagging (DE-588)7629989-2 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Social Tagging (DE-588)7629989-2 s Empfehlungssystem (DE-588)7511891-9 s DE-604 Erscheint auch als Online-Ausgabe 10.1007/978-3-658-01948-8 https://doi.org/10.1007/978-3-658-01948-8 Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025963223&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gedikli, Fatih Recommender systems and the social web leveraging tagging data for recommender systems Empfehlungssystem (DE-588)7511891-9 gnd Social Tagging (DE-588)7629989-2 gnd |
| subject_GND | (DE-588)7511891-9 (DE-588)7629989-2 (DE-588)4113937-9 |
| title | Recommender systems and the social web leveraging tagging data for recommender systems |
| title_auth | Recommender systems and the social web leveraging tagging data for recommender systems |
| title_exact_search | Recommender systems and the social web leveraging tagging data for recommender systems |
| title_full | Recommender systems and the social web leveraging tagging data for recommender systems Fatih Gedikli |
| title_fullStr | Recommender systems and the social web leveraging tagging data for recommender systems Fatih Gedikli |
| title_full_unstemmed | Recommender systems and the social web leveraging tagging data for recommender systems Fatih Gedikli |
| title_short | Recommender systems and the social web |
| title_sort | recommender systems and the social web leveraging tagging data for recommender systems |
| title_sub | leveraging tagging data for recommender systems |
| topic | Empfehlungssystem (DE-588)7511891-9 gnd Social Tagging (DE-588)7629989-2 gnd |
| topic_facet | Empfehlungssystem Social Tagging Hochschulschrift |
| url | https://doi.org/10.1007/978-3-658-01948-8 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025963223&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT gediklifatih recommendersystemsandthesocialwebleveragingtaggingdataforrecommendersystems |
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