Empfehlungssysteme: Recommender Systems - Grundlagen, Konzepte und Lösungen
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | German |
| Published: |
Wiesbaden
Vieweg + Teubner
2009
|
| Edition: | 1. Aufl. |
| Series: | Studium
IT-Management und -Anwendungen |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XII, 174 S. Ill., graph. Darst., Kt. 24 cm |
| ISBN: | 3834805688 9783834805683 |
Staff View
MARC
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| 100 | 1 | |a Klahold, André |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Empfehlungssysteme |b Recommender Systems - Grundlagen, Konzepte und Lösungen |c André Klahold |
| 250 | |a 1. Aufl. | ||
| 264 | 1 | |a Wiesbaden |b Vieweg + Teubner |c 2009 | |
| 300 | |a XII, 174 S. |b Ill., graph. Darst., Kt. |c 24 cm | ||
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Record in the Search Index
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|---|---|
| adam_text | Inhaltsverzeichnis
1 Überblick..................................................................................................1
1.1 Grundbegriffe...................................................................................1
1.1.1 Empfehlungssystem...................................................................1
1.1.2 Personalisierung.........................................................................3
1.1.3 Suchverfahren.............................................................................3
1.2 Anwendungsgebiete.........................................................................4
1.2.1 Inhalte..........................................................................................5
1.3 Entwicklungsgeschichte.................................................................16
2 Grundlagen............................................................................................21
2.1 Fachtermini.......................................................................................21
2.1.1 Allgemein..................................................................................21
2.1.2 Eigenschaftsanalyse..................................................................23
2.1.3 Metadaten..................................................................................28
2.1.4 Linguistik...................................................................................32
3 Methoden von Empfehlungssystemen...............................................37
3.1 Die Qualität von Empfehlungen...................................................37
3.1.1 Nützlichkeit als Maßstab.........................................................38
3.1.2 Ähnlichkeit als Maßstab..........................................................39
3.1.3 Expertenempfehlungen und Referenz-Daten.......................39
3.1.4
Precision
und
Recall
.................................................................40
3.2 Content
Based Filtering..................................................................
42
3.2.1 Eigenschaftsanalyse..................................................................42
3.2.2 Eigenschaftsanalyse am Beispiel von Textdokumenten......42
3.2.3 Repräsentation der Eigenschaften..........................................56
3.2.4 Ähnliche Elemente als Empfehlungen..................................58
3.2.5 Alternative Verfahren..............................................................59
3.3
Collaborative Filtering....................................................................
62
IX
Inhaltsverzeichnis
3.3.1 Der benutzerbezogene Algorithmus......................................63
3.3.2 Der elementbasierte Algorithmus..........................................64
3.3.3 Modell- und speicherbasiertes Verfahren.............................65
3.3.4 Nachteile des
Collaborative
Filtering....................................
66
3.4 Hybride Verfahren..........................................................................68
3.5 Ähnlichkeit als Selektionskriterium..............................................68
3.5.1 Distanz und Ähnlichkeit..........................................................71
3.5.2 Cosinus.......................................................................................71
3.5.3
Pearson
Korrelationskoeffizient.............................................72
3.5.4
Overlap
Koeffizient..................................................................73
3.5.5
Dice
Koeffizient.........................................................................73
3.5.6 Jaccard Koeffizient....................................................................74
3.5.7 Euklidscher Abstand................................................................75
3.5.8 Mutual Information..................................................................75
3.5.9
Nearest Neighbours.................................................................
76
3.6 Klassifikationsverfahren.................................................................77
3.6.1 Minimum
Description Length
(MDL)...................................77
3.6.2 Naiver Bayes-Klassifikator......................................................79
3.6.3 Bayes sches Netz.......................................................................80
3.6.4 ID3...............................................................................................82
3.6.5 K-Means-Clustering.................................................................86
4 Anwendungen.......................................................................................87
4.1
Collaborative
Filtering-Systeme....................................................89
4.1.1
Tapestry
.....................................................................................89
4.1.2 Ringo..........................................................................................90
4.1.3 GroupLens.................................................................................92
4.1.4
Siteseer
.......................................................................................93
4.1.5
Jester
(Eigentaste).....................................................................94
4.1.6 Amazon......................................................................................95
4.1.7 SurfLen.......................................................................................96
4.1.8 PocketLens.................................................................................98
4.1.9
PACT
........................................................................................100
X
Inhaltsverzeichnis
4.2 Content Based Filtering-Systeme................................................102
4.2.1 The Information
lens
..............................................................102
4.2.2 Infoscope..................................................................................103
4.2.3 Newsweeder............................................................................104
4.2.4
Letizia
.......................................................................................105
4.2.5 WebWatcher............................................................................107
4.2.6 Syskill & Webert.....................................................................109
4.2.7
Remembrance
Agent..............................................................110
4.2.8 InfoFinder................................................................................111
4.2.9 Amalthaea................................................................................113
4.2.10 AgentDLS..............................................................................114
4.2.11 Webmate................................................................................116
4.2.12
SLIDER
...................................................................................117
4.2.13 LexicalChainer......................................................................119
4.2.14 NewsDude.............................................................................121
4.2.15
SIFT
.........................................................................................122
4.2.16
Watson...................................................................................
124
4.2.17
LIBRA
.....................................................................................126
4.2.18 Margin Notes........................................................................127
4.2.19
Jimminy
..................................................................................128
4.2.20
SUITOR
..................................................................................129
4.2.21
PRES.......................................................................................
130
4.2.22
WebSail
..................................................................................132
4.2.23
WAIR
......................................................................................133
4.2.24
Powerscout
............................................................................135
4.2.25
CALVIN
.................................................................................136
4.2.26
WordSieve
.............................................................................138
4.2.27
MetaMarker
...........................................................................140
4.2.28
WebTop
..................................................................................141
4.2.29
INFOS
.....................................................................................142
4.3
Hybride
Systeme...........................................................................144
4.3.1
Fab
............................................................................................144
XI
Inhaltsverzeichnis
4.3.2 PHOAKS..................................................................................145
4.3.3
Let s Browse............................................................................
146
4.3.4 CASMIR...................................................................................148
4.3.5 LaboUr.....................................................................................149
4.3.6 Tango........................................................................................150
4.3.7 Nakif.........................................................................................152
4.3.8 MovieLens...............................................................................153
Literaturverzeichnis................................................................................155
Abbildungsverzeichnis...........................................................................167
Stichwortverzeichnis...............................................................................171
XII
|
| any_adam_object | 1 |
| author | Klahold, André |
| author_facet | Klahold, André |
| author_role | aut |
| author_sort | Klahold, André |
| author_variant | a k ak |
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| dewey-full | 006.332 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.332 |
| dewey-search | 006.332 |
| dewey-sort | 16.332 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Wirtschaftswissenschaften |
| edition | 1. Aufl. |
| format | Book |
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| isbn | 3834805688 9783834805683 |
| language | German |
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| physical | XII, 174 S. Ill., graph. Darst., Kt. 24 cm |
| publishDate | 2009 |
| publishDateSearch | 2009 |
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| publisher | Vieweg + Teubner |
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| series2 | Studium IT-Management und -Anwendungen |
| spelling | Klahold, André Verfasser aut Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen André Klahold 1. Aufl. Wiesbaden Vieweg + Teubner 2009 XII, 174 S. Ill., graph. Darst., Kt. 24 cm txt rdacontent n rdamedia nc rdacarrier Studium IT-Management und -Anwendungen Empfehlungssystem (DE-588)7511891-9 gnd rswk-swf Content Management (DE-588)4673954-3 gnd rswk-swf Kollaborative Filterung (DE-588)7512839-1 gnd rswk-swf Informationsfilterung (DE-588)4807493-7 gnd rswk-swf Empfehlungssystem (DE-588)7511891-9 s DE-604 Kollaborative Filterung (DE-588)7512839-1 s Informationsfilterung (DE-588)4807493-7 s Content Management (DE-588)4673954-3 s Erscheint auch als Online-Ausgabe 978-3-8348-9558-5 Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017143858&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Klahold, André Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen Empfehlungssystem (DE-588)7511891-9 gnd Content Management (DE-588)4673954-3 gnd Kollaborative Filterung (DE-588)7512839-1 gnd Informationsfilterung (DE-588)4807493-7 gnd |
| subject_GND | (DE-588)7511891-9 (DE-588)4673954-3 (DE-588)7512839-1 (DE-588)4807493-7 |
| title | Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen |
| title_auth | Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen |
| title_exact_search | Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen |
| title_full | Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen André Klahold |
| title_fullStr | Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen André Klahold |
| title_full_unstemmed | Empfehlungssysteme Recommender Systems - Grundlagen, Konzepte und Lösungen André Klahold |
| title_short | Empfehlungssysteme |
| title_sort | empfehlungssysteme recommender systems grundlagen konzepte und losungen |
| title_sub | Recommender Systems - Grundlagen, Konzepte und Lösungen |
| topic | Empfehlungssystem (DE-588)7511891-9 gnd Content Management (DE-588)4673954-3 gnd Kollaborative Filterung (DE-588)7512839-1 gnd Informationsfilterung (DE-588)4807493-7 gnd |
| topic_facet | Empfehlungssystem Content Management Kollaborative Filterung Informationsfilterung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017143858&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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