Recommender systems and the social web: leveraging tagging data for recommender systems
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Electronic eBook |
| Language: | English |
| Published: |
Wiesbaden
Springer
2013
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| Subjects: | |
| Online Access: | DE-634 DE-Aug4 DE-M347 DE-92 DE-859 DE-473 DE-355 DE-703 DE-20 DE-29 DE-739 Volltext Inhaltsverzeichnis Abstract |
| Physical Description: | 1 Online-Ressource |
| ISBN: | 9783658019471 9783658019488 |
| DOI: | 10.1007/978-3-658-01948-8 |
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Record in the Search Index
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| adam_text |
RECOMMENDER SYSTEMS AND THE SOCIAL WEB
/ GEDIKLI, FATIH
: 2013
TABLE OF CONTENTS / INHALTSVERZEICHNIS
RECOMMENDER SYSTEMS
SOCIAL TAGGING
ALGORITHMS
EXPLANATIONS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
RECOMMENDER SYSTEMS AND THE SOCIAL WEB
/ GEDIKLI, FATIH
: 2013
ABSTRACT / INHALTSTEXT
THERE IS AN INCREASING DEMAND FOR RECOMMENDER SYSTEMS DUE TO THE
INFORMATION OVERLOAD USERS ARE FACING ON THE WEB. THE GOAL OF A
RECOMMENDER SYSTEM IS TO PROVIDE PERSONALIZED RECOMMENDATIONS OF
PRODUCTS OR SERVICES TO USERS. WITH THE ADVENT OF THE SOCIAL WEB,
USER-GENERATED CONTENT HAS ENRICHED THE SOCIAL DIMENSION OF THE WEB. AS
USER-PROVIDED CONTENT DATA ALSO TELLS US SOMETHING ABOUT THE USER, ONE
CAN LEARN THE USER’S INDIVIDUAL PREFERENCES FROM THE SOCIAL WEB. THIS
OPENS UP COMPLETELY NEW OPPORTUNITIES AND CHALLENGES FOR RECOMMENDER
SYSTEMS RESEARCH. FATIH GEDIKLI DEALS WITH THE QUESTION OF HOW
USER-PROVIDED TAGGING DATA CAN BE USED TO BUILD BETTER RECOMMENDER
SYSTEMS. A TAG RECOMMENDER ALGORITHM IS PROPOSED WHICH RECOMMENDS TAGS
FOR USERS TO ANNOTATE THEIR FAVORITE ONLINE RESOURCES. THE AUTHOR ALSO
PROPOSES ALGORITHMS WHICH EXPLOIT THE USER-PROVIDED TAGGING DATA AND
PRODUCE MORE ACCURATE RECOMMENDATIONS. ON THE BASIS OF THIS IDEA, HE
SHOWS HOW TAGS CAN BE USED TO EXPLAIN TO THE USER THE AUTOMATICALLY
GENERATED RECOMMENDATIONS IN A CLEAR AND INTUITIVELY UNDERSTANDABLE
FORM. WITH HIS BOOK, FATIH GEDIKLI GIVES US AN OUTLOOK ON THE NEXT
GENERATION OF RECOMMENDATION SYSTEMS IN THE SOCIAL WEB SPHERE. CONTENTS
- RECOMMENDER SYSTEMS - SOCIAL TAGGING - ALGORITHMS -
EXPLANATIONS TARGET GROUPS RESEARCHERS AND
STUDENTS OF COMPUTER SCIENCE COMPUTER AND WEB
PROGRAMMERS THE AUTHOR DR. FATIH GEDIKLI IS A RESEARCH ASSISTANT IN
COMPUTER SCIENCE AT TU DORTMUND, GERMANY
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. |
| any_adam_object | 1 |
| author | Gedikli, Fatih |
| author_GND | (DE-588)13803141X |
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| author_role | aut |
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| author_variant | f g fg |
| building | Verbundindex |
| bvnumber | BV040953427 |
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| dewey-full | 006.312 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.312 |
| dewey-search | 006.312 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1007/978-3-658-01948-8 |
| format | Thesis Electronic eBook |
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| 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 |
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