Recommender Systems:
Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Somerset
Wiley
2014
|
| Edition: | 1st ed |
| Subjects: | |
| Summary: | Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior |
| Item Description: | Description based on publisher supplied metadata and other sources |
| Physical Description: | 1 online resource (253 pages) |
| ISBN: | 9781119054245 9781119054252 |
Staff View
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV043891945 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 161123s2014 |||| o||u| ||||||eng d | ||
| 020 | |a 9781119054245 |9 978-1-119-05424-5 | ||
| 020 | |a 9781119054252 |c Print |9 978-1-119-05425-2 | ||
| 035 | |a (ZDB-30-PQE)EBC1884200 | ||
| 035 | |a (ZDB-89-EBL)EBL1884200 | ||
| 035 | |a (ZDB-38-EBR)ebr10995110 | ||
| 035 | |a (OCoLC)897810260 | ||
| 035 | |a (DE-599)BVBBV043891945 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 082 | 0 | |a 001.64 | |
| 100 | 1 | |a Kembellec, Gérald |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Recommender Systems |
| 250 | |a 1st ed | ||
| 264 | 1 | |a Somerset |b Wiley |c 2014 | |
| 264 | 4 | |c © 2014 | |
| 300 | |a 1 online resource (253 pages) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 520 | |a Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior | ||
| 650 | 4 | |a Recommender systems (Information filtering) | |
| 700 | 1 | |a Chartron, Ghislaine |e Sonstige |4 oth | |
| 700 | 1 | |a Saleh, Imad |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Kembellec, Gérald |t Recommender Systems |
| 912 | |a ZDB-30-PQE |a ZDB-38-ESG | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-029301326 | ||
Record in the Search Index
| _version_ | 1804176794035683328 |
|---|---|
| any_adam_object | |
| author | Kembellec, Gérald |
| author_facet | Kembellec, Gérald |
| author_role | aut |
| author_sort | Kembellec, Gérald |
| author_variant | g k gk |
| building | Verbundindex |
| bvnumber | BV043891945 |
| collection | ZDB-30-PQE ZDB-38-ESG |
| ctrlnum | (ZDB-30-PQE)EBC1884200 (ZDB-89-EBL)EBL1884200 (ZDB-38-EBR)ebr10995110 (OCoLC)897810260 (DE-599)BVBBV043891945 |
| dewey-full | 001.64 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 001 - Knowledge |
| dewey-raw | 001.64 |
| dewey-search | 001.64 |
| dewey-sort | 11.64 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Allgemeines |
| edition | 1st ed |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02092nmm a2200409zc 4500</leader><controlfield tag="001">BV043891945</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">161123s2014 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119054245</subfield><subfield code="9">978-1-119-05424-5</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119054252</subfield><subfield code="c">Print</subfield><subfield code="9">978-1-119-05425-2</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC1884200</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL1884200</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-38-EBR)ebr10995110</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)897810260</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043891945</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">001.64</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kembellec, Gérald</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Recommender Systems</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Somerset</subfield><subfield code="b">Wiley</subfield><subfield code="c">2014</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2014</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (253 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Recommender systems (Information filtering)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chartron, Ghislaine</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Saleh, Imad</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Kembellec, Gérald</subfield><subfield code="t">Recommender Systems</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield><subfield code="a">ZDB-38-ESG</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-029301326</subfield></datafield></record></collection> |
| id | DE-604.BV043891945 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:37:50Z |
| institution | BVB |
| isbn | 9781119054245 9781119054252 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029301326 |
| oclc_num | 897810260 |
| open_access_boolean | |
| physical | 1 online resource (253 pages) |
| psigel | ZDB-30-PQE ZDB-38-ESG |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Wiley |
| record_format | marc |
| spelling | Kembellec, Gérald Verfasser aut Recommender Systems 1st ed Somerset Wiley 2014 © 2014 1 online resource (253 pages) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior Recommender systems (Information filtering) Chartron, Ghislaine Sonstige oth Saleh, Imad Sonstige oth Erscheint auch als Druck-Ausgabe Kembellec, Gérald Recommender Systems |
| spellingShingle | Kembellec, Gérald Recommender Systems Recommender systems (Information filtering) |
| title | Recommender Systems |
| title_auth | Recommender Systems |
| title_exact_search | Recommender Systems |
| title_full | Recommender Systems |
| title_fullStr | Recommender Systems |
| title_full_unstemmed | Recommender Systems |
| title_short | Recommender Systems |
| title_sort | recommender systems |
| topic | Recommender systems (Information filtering) |
| topic_facet | Recommender systems (Information filtering) |
| work_keys_str_mv | AT kembellecgerald recommendersystems AT chartronghislaine recommendersystems AT salehimad recommendersystems |