{"id":"https://openalex.org/W3196185722","doi":"https://doi.org/10.1145/3447548.3470825","title":"All You Need to Know to Build a Product Knowledge Graph","display_name":"All You Need to Know to Build a Product Knowledge Graph","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3196185722","doi":"https://doi.org/10.1145/3447548.3470825","mag":"3196185722"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3470825","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3470825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","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/A5089887413","display_name":"Nasser Zalmout","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nasser Zalmout","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011355966","display_name":"Chenwei Zhang","orcid":"https://orcid.org/0000-0002-0606-3649"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenwei Zhang","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113747782","display_name":"Xian Li","orcid":"https://orcid.org/0000-0001-7660-5290"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xian Li","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047270852","display_name":"Yan Liang","orcid":"https://orcid.org/0000-0002-5136-4432"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Liang","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115444875","display_name":"Xin Dong","orcid":"https://orcid.org/0009-0001-4042-628X"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Luna Dong","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5089887413"],"corresponding_institution_ids":["https://openalex.org/I1311688040"],"apc_list":null,"apc_paid":null,"fwci":3.943,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.94665199,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4090","last_page":"4091"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994999766349792,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9958000183105469,"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/T10028","display_name":"Topic Modeling","score":0.9937000274658203,"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/knowledge-graph","display_name":"Knowledge graph","score":0.8022410273551941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7790131568908691},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.6366057395935059},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6161994338035583},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.5509742498397827},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5286099314689636},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5198779106140137},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4510100781917572},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4240269362926483},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34551966190338135},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.3370763063430786},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3319118618965149},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3007081151008606},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10918471217155457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09079843759536743}],"concepts":[{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.8022410273551941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7790131568908691},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.6366057395935059},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6161994338035583},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.5509742498397827},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5286099314689636},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5198779106140137},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4510100781917572},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4240269362926483},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34551966190338135},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3370763063430786},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3319118618965149},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3007081151008606},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10918471217155457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09079843759536743},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3470825","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3470825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1982876325","https://openalex.org/W2740070748","https://openalex.org/W2805173585","https://openalex.org/W2945748862","https://openalex.org/W2946532448","https://openalex.org/W2951865668","https://openalex.org/W2970923431","https://openalex.org/W3036762099","https://openalex.org/W3080562041","https://openalex.org/W3087568487","https://openalex.org/W3093133157","https://openalex.org/W3100195825","https://openalex.org/W3104609290","https://openalex.org/W3105298925"],"related_works":["https://openalex.org/W4292070284","https://openalex.org/W2916853871","https://openalex.org/W2923818335","https://openalex.org/W4310444679","https://openalex.org/W3191833430","https://openalex.org/W3016646566","https://openalex.org/W4385459432","https://openalex.org/W4210315291","https://openalex.org/W3193273225","https://openalex.org/W68685461"],"abstract_inverted_index":{"Knowledge":[0],"graphs":[1,19],"have":[2,20],"been":[3],"pivotal":[4],"in":[5,26,78,88,96],"supporting":[6],"downstream":[7],"applications":[8],"like":[9],"search,":[10],"recommendation,":[11],"and":[12,46,59,75,101],"question":[13],"answering,":[14],"among":[15],"others.":[16],"Therefore,":[17],"knowledge":[18,34,41,66,85],"naturally":[21],"become":[22],"key":[23],"enabling":[24],"technologies":[25],"e-Commerce":[27,111],"platforms.":[28,112],"Developing":[29],"a":[30,82],"high":[31],"coverage":[32],"product":[33,60,84],"graph":[35],"is":[36],"more":[37],"challenging":[38],"than":[39],"generic":[40],"graphs.":[42,67],"The":[43],"highly":[44],"specific":[45,108],"complex":[47],"domain,":[48],"the":[49,56,64,93,107],"sparsity":[50],"of":[51,110],"training":[52],"data,":[53],"along":[54],"with":[55],"dynamic":[57],"taxonomies":[58],"types,":[61],"can":[62],"constrain":[63],"resulting":[65],"In":[68],"this":[69,89],"tutorial":[70],"we":[71],"present":[72],"best":[73],"practices":[74],"ML":[76],"innovations":[77],"industry":[79],"towards":[80],"building":[81],"scalable":[83],"graph.":[86],"Contributions":[87],"domain":[90],"benefit":[91],"from":[92],"general":[94],"literature":[95],"areas":[97],"including":[98],"information":[99],"extraction":[100],"data":[102],"mining,":[103],"tailored":[104],"to":[105],"address":[106],"characteristics":[109]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
