{"id":"https://openalex.org/W1963834128","doi":"https://doi.org/10.1145/1593254.1593268","title":"Overcoming small-size training set problem in content-based recommendation","display_name":"Overcoming small-size training set problem in content-based recommendation","publication_year":2009,"publication_date":"2009-08-12","ids":{"openalex":"https://openalex.org/W1963834128","doi":"https://doi.org/10.1145/1593254.1593268","mag":"1963834128"},"language":"en","primary_location":{"id":"doi:10.1145/1593254.1593268","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1593254.1593268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th International Conference on Electronic Commerce","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101445618","display_name":"Yen\u2010Hsien Lee","orcid":"https://orcid.org/0000-0003-0979-0515"},"institutions":[{"id":"https://openalex.org/I183570559","display_name":"National Chiayi University","ror":"https://ror.org/04gknbs13","country_code":"TW","type":"education","lineage":["https://openalex.org/I183570559"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yen-Hsien Lee","raw_affiliation_strings":["National Chiayi University, Chiayi, Taiwan, R.O.C","National Chiayi University, Chiayi, Taiwan (R.O.C.)#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chiayi University, Chiayi, Taiwan, R.O.C","institution_ids":["https://openalex.org/I183570559"]},{"raw_affiliation_string":"National Chiayi University, Chiayi, Taiwan (R.O.C.)#TAB#","institution_ids":["https://openalex.org/I183570559"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109045325","display_name":"Tsang-Hsiang Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I92582371","display_name":"Southern Taiwan University of Science and Technology","ror":"https://ror.org/0029n1t76","country_code":"TW","type":"education","lineage":["https://openalex.org/I92582371"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsang-Hsiang Cheng","raw_affiliation_strings":["Southern Taiwan University, Tainan, Taiwan, R.O.C","Southern Taiwan University, Tainan, Taiwan, R.O.C.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Taiwan University, Tainan, Taiwan, R.O.C","institution_ids":["https://openalex.org/I92582371"]},{"raw_affiliation_string":"Southern Taiwan University, Tainan, Taiwan, R.O.C.#TAB#","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030124885","display_name":"Ci-Wei Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ci-Wei Lan","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019134461","display_name":"Chih\u2010Ping Wei","orcid":"https://orcid.org/0000-0003-4150-3926"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Ping Wei","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006784495","display_name":"Paul Jen\u2010Hwa Hu","orcid":"https://orcid.org/0000-0002-4981-895X"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Jen-Hwa Hu","raw_affiliation_strings":["University of Utah, Salt Lake City, UT","University of Utah; Salt Lake City; UT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah, Salt Lake City, UT","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"University of Utah; Salt Lake City; UT","institution_ids":["https://openalex.org/I223532165"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"99","last_page":"106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8078430891036987},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.789755642414093},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6583629846572876},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6488338708877563},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5464301705360413},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5157142281532288},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4333195686340332},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.42594683170318604},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.37691447138786316},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.357651025056839},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27835774421691895},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0715765655040741}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8078430891036987},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.789755642414093},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6583629846572876},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6488338708877563},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5464301705360413},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5157142281532288},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4333195686340332},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.42594683170318604},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.37691447138786316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.357651025056839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27835774421691895},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0715765655040741},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1593254.1593268","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1593254.1593268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th International Conference on Electronic Commerce","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G4807054935","display_name":null,"funder_award_id":"NSC 97-2410-H-218-017-MY2","funder_id":"https://openalex.org/F4320321040","funder_display_name":"National Science Council"}],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1489725718","https://openalex.org/W1493526108","https://openalex.org/W1673941785","https://openalex.org/W1861993554","https://openalex.org/W1966553486","https://openalex.org/W1981166623","https://openalex.org/W1983078185","https://openalex.org/W1986913017","https://openalex.org/W1997136459","https://openalex.org/W2004338242","https://openalex.org/W2035754578","https://openalex.org/W2042281163","https://openalex.org/W2043403353","https://openalex.org/W2067946179","https://openalex.org/W2085937320","https://openalex.org/W2093799708","https://openalex.org/W2099480244","https://openalex.org/W2100719534","https://openalex.org/W2110325612","https://openalex.org/W2127480961","https://openalex.org/W2147654806","https://openalex.org/W2154642048","https://openalex.org/W2163557029","https://openalex.org/W2170654002","https://openalex.org/W2171960770","https://openalex.org/W2188897822","https://openalex.org/W2766736793","https://openalex.org/W2911640577","https://openalex.org/W4232980324","https://openalex.org/W4242129433","https://openalex.org/W6614676750","https://openalex.org/W6637259173"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2735929803","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W4376854386","https://openalex.org/W1966742602"],"abstract_inverted_index":{"Effective,":[0],"personalized":[1],"recommendations":[2,125],"are":[3],"central":[4],"to":[5,18,44,50,99,137],"cross-selling,":[6],"a":[7,76,87,95,106,128,133],"common":[8,107],"business":[9],"strategy":[10],"that":[11,93],"suggests":[12],"additional":[13],"items":[14,43],"(products":[15],"or":[16],"services)":[17],"customers":[19],"for":[20,32,123],"their":[21,67],"consideration.":[22],"Content-based":[23],"recommendation":[24,58,91,112],"and":[25,69,126],"collaborative":[26,88],"filtering":[27],"represent":[28],"two":[29],"salient":[30],"approaches":[31],"automated":[33],"recommendations.":[34],"The":[35],"content-based":[36,57,89,111,130],"approach":[37,98],"uses":[38,94],"essential":[39],"features":[40],"(attributes)":[41],"of":[42,53,75,79,119],"make":[45],"recommendations,":[46],"without":[47],"making":[48],"reference":[49],"the":[51,73,101,110,117,120,141,147],"preferences":[52],"other":[54],"customers.":[55],"Although":[56],"techniques":[59],"have":[60],"been":[61],"shown":[62],"effective":[63],"in":[64],"various":[65],"scenarios,":[66],"utilities":[68],"value":[70],"depend":[71],"on":[72],"availability":[74],"large":[77],"number":[78],"training":[80,103],"examples.":[81],"In":[82],"this":[83],"study,":[84],"we":[85],"propose":[86],"(COCO)":[90],"technique":[92,122,131,144],"collaboration-based":[96],"expansion":[97],"address":[100],"small-size":[102],"set":[104],"problem,":[105],"challenge":[108],"faced":[109],"approach.":[113],"We":[114],"empirically":[115],"examine":[116],"effectiveness":[118],"proposed":[121,142],"book":[124],"include":[127],"pure":[129],"as":[132],"performance":[134],"benchmark.":[135],"According":[136],"our":[138],"evaluation":[139],"results,":[140],"COCO":[143],"substantially":[145],"outperforms":[146],"benchmark":[148],"technique.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
