Computational intelligence meets the NetFlix prize

Computational intelligence meets the NetFlix prize

The NetFlix Prize is a research contest that will award 1 Million to the first group to improve NetFlixpsilas movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Meuth, R.J., Robinette, P., Wunsch, D.C.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
History
Joints
Motion pictures
Neurons
Subspace constraints
Training
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 691
container_issue
container_start_page 686
container_title
container_volume 10
creator Meuth, R.J.
Robinette, P.
Wunsch, D.C.
description The NetFlix Prize is a research contest that will award 1 Million to the first group to improve NetFlixpsilas movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that can predict how a customer will rate a given movie on a scale of 1 to 5. An architecture is presented that utilizes the fuzzy-adaptive resonance theory clustering method to create an interesting set of data attributes that are input to a neural network for mapping to a classification.
doi_str_mv 10.1109/IJCNN.2008.4633869
format Conference Proceeding
fullrecord <record><control><sourceid>proquest_6IE</sourceid><recordid>TN_cdi_proquest_miscellaneous_34476458</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4633869</ieee_id><sourcerecordid>34476458</sourcerecordid><originalsourceid>FETCH-LOGICAL-i206t-463ac2912b7337cb05c33aa382efa8016b72f5ec5f949bec8922a98bfb76eb6a3</originalsourceid><addsrcrecordid>eNpFkD1PwzAYhM2XRFv4A7BkYkuw_TqOPaKIQlEVFpgj23oDRvkidiXg1xOpRSx3w51Oj46QK0Yzxqi-3TyVVZVxSlUmJICS-ogsmeBCMMWZPCaLWVkqBC1O_gOqTv8C0HBOliF8UMpBa1gQXg7duIsm-qE3beL7iG3r37B3mHSIMSTxHZMK47r1X8k4-R-8IGeNaQNeHnxFXtf3L-Vjun1-2JR329RzKmM6ExrHNeO2ACicpbkDMAYUx8YoyqQteJOjyxsttEWnNOdGK9vYQqKVBlbkZr87TsPnDkOsOx_cjGd6HHahBiEKKXI1F6_3RY-I9czYmem7PjwEvyw4VeE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>34476458</pqid></control><display><type>conference_proceeding</type><title>Computational intelligence meets the NetFlix prize</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Meuth, R.J. ; Robinette, P. ; Wunsch, D.C.</creator><creatorcontrib>Meuth, R.J. ; Robinette, P. ; Wunsch, D.C.</creatorcontrib><description>The NetFlix Prize is a research contest that will award 1 Million to the first group to improve NetFlixpsilas movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that can predict how a customer will rate a given movie on a scale of 1 to 5. An architecture is presented that utilizes the fuzzy-adaptive resonance theory clustering method to create an interesting set of data attributes that are input to a neural network for mapping to a classification.</description><identifier>ISSN: 2161-4393</identifier><identifier>ISSN: 1522-4899</identifier><identifier>ISBN: 1424418208</identifier><identifier>ISBN: 9781424418206</identifier><identifier>ISBN: 9781424432196</identifier><identifier>ISBN: 1424432197</identifier><identifier>EISSN: 2161-4407</identifier><identifier>EISBN: 1424418216</identifier><identifier>EISBN: 9781424418213</identifier><identifier>DOI: 10.1109/IJCNN.2008.4633869</identifier><language>eng</language><publisher>IEEE</publisher><subject>Artificial neural networks ; History ; Joints ; Motion pictures ; Neurons ; Subspace constraints ; Training</subject><ispartof>2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008, Vol.10, p.686-691</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4633869$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,314,777,781,786,787,2052,27905,27906,54901</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4633869$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Meuth, R.J.</creatorcontrib><creatorcontrib>Robinette, P.</creatorcontrib><creatorcontrib>Wunsch, D.C.</creatorcontrib><title>Computational intelligence meets the NetFlix prize</title><title>2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)</title><addtitle>IJCNN</addtitle><description>The NetFlix Prize is a research contest that will award 1 Million to the first group to improve NetFlixpsilas movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that can predict how a customer will rate a given movie on a scale of 1 to 5. An architecture is presented that utilizes the fuzzy-adaptive resonance theory clustering method to create an interesting set of data attributes that are input to a neural network for mapping to a classification.</description><subject>Artificial neural networks</subject><subject>History</subject><subject>Joints</subject><subject>Motion pictures</subject><subject>Neurons</subject><subject>Subspace constraints</subject><subject>Training</subject><issn>2161-4393</issn><issn>1522-4899</issn><issn>2161-4407</issn><isbn>1424418208</isbn><isbn>9781424418206</isbn><isbn>9781424432196</isbn><isbn>1424432197</isbn><isbn>1424418216</isbn><isbn>9781424418213</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkD1PwzAYhM2XRFv4A7BkYkuw_TqOPaKIQlEVFpgj23oDRvkidiXg1xOpRSx3w51Oj46QK0Yzxqi-3TyVVZVxSlUmJICS-ogsmeBCMMWZPCaLWVkqBC1O_gOqTv8C0HBOliF8UMpBa1gQXg7duIsm-qE3beL7iG3r37B3mHSIMSTxHZMK47r1X8k4-R-8IGeNaQNeHnxFXtf3L-Vjun1-2JR329RzKmM6ExrHNeO2ACicpbkDMAYUx8YoyqQteJOjyxsttEWnNOdGK9vYQqKVBlbkZr87TsPnDkOsOx_cjGd6HHahBiEKKXI1F6_3RY-I9czYmem7PjwEvyw4VeE</recordid><startdate>20080601</startdate><enddate>20080601</enddate><creator>Meuth, R.J.</creator><creator>Robinette, P.</creator><creator>Wunsch, D.C.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20080601</creationdate><title>Computational intelligence meets the NetFlix prize</title><author>Meuth, R.J. ; Robinette, P. ; Wunsch, D.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i206t-463ac2912b7337cb05c33aa382efa8016b72f5ec5f949bec8922a98bfb76eb6a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Artificial neural networks</topic><topic>History</topic><topic>Joints</topic><topic>Motion pictures</topic><topic>Neurons</topic><topic>Subspace constraints</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Meuth, R.J.</creatorcontrib><creatorcontrib>Robinette, P.</creatorcontrib><creatorcontrib>Wunsch, D.C.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Meuth, R.J.</au><au>Robinette, P.</au><au>Wunsch, D.C.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Computational intelligence meets the NetFlix prize</atitle><btitle>2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)</btitle><stitle>IJCNN</stitle><date>2008-06-01</date><risdate>2008</risdate><volume>10</volume><spage>686</spage><epage>691</epage><pages>686-691</pages><issn>2161-4393</issn><issn>1522-4899</issn><eissn>2161-4407</eissn><isbn>1424418208</isbn><isbn>9781424418206</isbn><isbn>9781424432196</isbn><isbn>1424432197</isbn><eisbn>1424418216</eisbn><eisbn>9781424418213</eisbn><abstract>The NetFlix Prize is a research contest that will award 1 Million to the first group to improve NetFlixpsilas movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that can predict how a customer will rate a given movie on a scale of 1 to 5. An architecture is presented that utilizes the fuzzy-adaptive resonance theory clustering method to create an interesting set of data attributes that are input to a neural network for mapping to a classification.</abstract><pub>IEEE</pub><doi>10.1109/IJCNN.2008.4633869</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 2161-4393
ispartof 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008, Vol.10, p.686-691
issn 2161-4393
1522-4899
2161-4407
language eng
recordid cdi_proquest_miscellaneous_34476458
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Artificial neural networks
History
Joints
Motion pictures
Neurons
Subspace constraints
Training
title Computational intelligence meets the NetFlix prize
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T13%3A16%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Computational%20intelligence%20meets%20the%20NetFlix%20prize&rft.btitle=2008%20IEEE%20International%20Joint%20Conference%20on%20Neural%20Networks%20(IEEE%20World%20Congress%20on%20Computational%20Intelligence)&rft.au=Meuth,%20R.J.&rft.date=2008-06-01&rft.volume=10&rft.spage=686&rft.epage=691&rft.pages=686-691&rft.issn=2161-4393&rft.eissn=2161-4407&rft.isbn=1424418208&rft.isbn_list=9781424418206&rft.isbn_list=9781424432196&rft.isbn_list=1424432197&rft_id=info:doi/10.1109/IJCNN.2008.4633869&rft_dat=%3Cproquest_6IE%3E34476458%3C/proquest_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424418216&rft.eisbn_list=9781424418213&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=34476458&rft_id=info:pmid/&rft_ieee_id=4633869&rfr_iscdi=true