{"id":"https://openalex.org/W2894039884","doi":"https://doi.org/10.1145/3240323.3240381","title":"HOP-rec","display_name":"HOP-rec","publication_year":2018,"publication_date":"2018-09-27","ids":{"openalex":"https://openalex.org/W2894039884","doi":"https://doi.org/10.1145/3240323.3240381","mag":"2894039884"},"language":"en","primary_location":{"id":"doi:10.1145/3240323.3240381","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240323.3240381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","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/A5014519159","display_name":"Jheng-Hong Yang","orcid":"https://orcid.org/0000-0001-5469-312X"},"institutions":[{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Jheng-Hong Yang","raw_affiliation_strings":["Academia Sinica, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Academia Sinica, Taipei, Taiwan","institution_ids":["https://openalex.org/I84653119"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102019603","display_name":"Chih-Ming Chen","orcid":"https://orcid.org/0000-0002-0290-4279"},"institutions":[{"id":"https://openalex.org/I87354575","display_name":"National Chengchi University","ror":"https://ror.org/03rqk8h36","country_code":"TW","type":"education","lineage":["https://openalex.org/I87354575"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Ming Chen","raw_affiliation_strings":["National Chengchi University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chengchi University, Taipei, Taiwan","institution_ids":["https://openalex.org/I87354575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017348970","display_name":"Chuan\u2010Ju Wang","orcid":"https://orcid.org/0000-0002-5281-2962"},"institutions":[{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chuan-Ju Wang","raw_affiliation_strings":["Academia Sinica, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Academia Sinica, Taipei, Taiwan","institution_ids":["https://openalex.org/I84653119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076203419","display_name":"Ming-Feng Tsai","orcid":"https://orcid.org/0000-0002-3358-8176"},"institutions":[{"id":"https://openalex.org/I87354575","display_name":"National Chengchi University","ror":"https://ror.org/03rqk8h36","country_code":"TW","type":"education","lineage":["https://openalex.org/I87354575"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ming-Feng Tsai","raw_affiliation_strings":["National Chengchi University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chengchi University, Taipei, Taiwan","institution_ids":["https://openalex.org/I87354575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014519159"],"corresponding_institution_ids":["https://openalex.org/I84653119"],"apc_list":null,"apc_paid":null,"fwci":37.698,"has_fulltext":false,"cited_by_count":197,"citation_normalized_percentile":{"value":0.9971915,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"140","last_page":"144"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9835000038146973,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9621999859809875,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7802107930183411},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7277485728263855},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6337527632713318},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5597166419029236},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5013515949249268},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.48212409019470215},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4607250988483429},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.4449988305568695},{"id":"https://openalex.org/keywords/stochastic-matrix","display_name":"Stochastic matrix","score":0.4333959221839905},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.42454269528388977},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38131946325302124},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3474549651145935},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27442431449890137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26926684379577637},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15083956718444824},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.12595519423484802},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.08714994788169861},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08616814017295837},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.08504506945610046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7802107930183411},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7277485728263855},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6337527632713318},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5597166419029236},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5013515949249268},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48212409019470215},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4607250988483429},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.4449988305568695},{"id":"https://openalex.org/C49555168","wikidata":"https://www.wikidata.org/wiki/Q176583","display_name":"Stochastic matrix","level":3,"score":0.4333959221839905},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.42454269528388977},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38131946325302124},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3474549651145935},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27442431449890137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26926684379577637},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15083956718444824},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.12595519423484802},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.08714994788169861},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08616814017295837},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.08504506945610046},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3240323.3240381","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240323.3240381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G3355224789","display_name":null,"funder_award_id":"107-2218-E-002-061","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W46938732","https://openalex.org/W1854214752","https://openalex.org/W1968598835","https://openalex.org/W1971040550","https://openalex.org/W2044051625","https://openalex.org/W2054141820","https://openalex.org/W2100235918","https://openalex.org/W2101409192","https://openalex.org/W2133299088","https://openalex.org/W2140310134","https://openalex.org/W2161984370","https://openalex.org/W2168108570","https://openalex.org/W2196920274","https://openalex.org/W2508504774","https://openalex.org/W2539586701","https://openalex.org/W2951320349","https://openalex.org/W2951781666","https://openalex.org/W2962917313","https://openalex.org/W2963185427","https://openalex.org/W4318211321"],"related_works":["https://openalex.org/W1597743604","https://openalex.org/W2038723108","https://openalex.org/W2033630974","https://openalex.org/W2794559785","https://openalex.org/W2325737604","https://openalex.org/W2950631682","https://openalex.org/W1973739845","https://openalex.org/W119752240","https://openalex.org/W2898722594","https://openalex.org/W2125326641"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"are":[2,18],"vital":[3],"ingredients":[4],"for":[5,86,108,121],"many":[6],"e-commerce":[7],"services.":[8],"In":[9,54],"the":[10,14,25,33,42,48,67,119,135,138],"literature,":[11],"two":[12,68],"of":[13,90,137,143],"most":[15],"popular":[16],"approaches":[17],"based":[19],"on":[20,76,140],"factorization":[21],"and":[22,39,41,62,117],"graph-based":[23],"models;":[24],"former":[26],"approach":[27,132],"captures":[28],"user":[29,123],"preferences":[30,46],"by":[31,51],"factorizing":[32,91],"observed":[34],"direct":[35],"interactions":[36],"between":[37],"users":[38],"items,":[40],"latter":[43],"extracts":[44],"indirect":[45],"from":[47],"graphs":[49],"constructed":[50],"user-item":[52,114],"interactions.":[53],"this":[55],"paper":[56],"we":[57,110],"present":[58],"HOP-Rec,":[59],"a":[60,77,92,98,112,141],"unified":[61],"efficient":[63],"method":[64,72,96],"that":[65,130],"incorporates":[66],"approaches.":[69],"The":[70],"proposed":[71],"involves":[73],"random":[74,125],"surfing":[75],"graph":[78],"to":[79,102],"harvest":[80],"high-order":[81,105],"information":[82,106],"among":[83],"neighborhood":[84],"items":[85],"each":[87,122],"user.":[88],"Instead":[89],"transition":[93],"matrix,":[94],"our":[95,131],"introduces":[97],"confidence":[99],"weighting":[100],"parameter":[101],"simulate":[103],"all":[104],"simultaneously,":[107],"which":[109],"maintain":[111],"sparse":[113],"interaction":[115],"matrix":[116,120],"enrich":[118],"using":[124],"walks.":[126],"Experimental":[127],"results":[128],"show":[129],"significantly":[133],"outperforms":[134],"state":[136],"art":[139],"range":[142],"large-scale":[144],"real-world":[145],"datasets.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":38},{"year":2021,"cited_by_count":46},{"year":2020,"cited_by_count":42},{"year":2019,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2018-10-05T00:00:00"}