{"id":"https://openalex.org/W4288280738","doi":"https://doi.org/10.1145/3331184.3331366","title":"Retrieving Multi-Entity Associations","display_name":"Retrieving Multi-Entity Associations","publication_year":2019,"publication_date":"2019-07-18","ids":{"openalex":"https://openalex.org/W4288280738","doi":"https://doi.org/10.1145/3331184.3331366"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3331184.3331366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"proceedings-article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1905.09052","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021562568","display_name":"Gloria Feher","orcid":null},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gloria Feher","raw_affiliation_strings":["Heidelberg University, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Heidelberg University, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018128415","display_name":"Andreas Spitz","orcid":"https://orcid.org/0000-0002-5282-6133"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Spitz","raw_affiliation_strings":["Heidelberg University, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Heidelberg University, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061021795","display_name":"Michael Gertz","orcid":"https://orcid.org/0000-0003-4530-6110"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Gertz","raw_affiliation_strings":["Heidelberg University, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Heidelberg University, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":62},"biblio":{"volume":null,"issue":null,"first_page":"1169","last_page":"1172"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Natural Language Processing","score":1.0,"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/T10028","display_name":"Natural Language Processing","score":1.0,"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/T10181","display_name":"Statistical Machine Translation and Natural Language Processing","score":0.9995,"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/T13083","display_name":"Automatic Keyword Extraction from Textual Data","score":0.9982,"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/word-embedding","display_name":"Word embedding","score":0.6705442},{"id":"https://openalex.org/keywords/word-representation","display_name":"Word Representation","score":0.590881},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named Entity Recognition","score":0.586432},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.55853206},{"id":"https://openalex.org/keywords/language-modeling","display_name":"Language Modeling","score":0.545681},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information Retrieval","score":0.530063},{"id":"https://openalex.org/keywords/topic-modeling","display_name":"Topic Modeling","score":0.528884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7812897},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.71920645},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.71209216},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6705442},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.64706635},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6431717},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6423168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6106378},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.55853206},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4070514},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12346479},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3331184.3331366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1905.09052","pdf_url":"https://arxiv.org/pdf/1905.09052","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.1905.09052","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1905.09052","pdf_url":"https://arxiv.org/pdf/1905.09052","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.56,"display_name":"Quality education","id":"https://metadata.un.org/sdg/4"}],"grants":[],"datasets":[],"versions":["https://openalex.org/W4288280738"],"referenced_works_count":9,"referenced_works":["https://openalex.org/W1880262756","https://openalex.org/W1984052055","https://openalex.org/W2055981215","https://openalex.org/W2087946919","https://openalex.org/W2337742504","https://openalex.org/W2341132943","https://openalex.org/W2799188490","https://openalex.org/W2962739339","https://openalex.org/W2998704965"],"related_works":["https://openalex.org/W947140380","https://openalex.org/W4287599800","https://openalex.org/W4286432911","https://openalex.org/W4245453790","https://openalex.org/W4230884544","https://openalex.org/W4214830338","https://openalex.org/W3216571906","https://openalex.org/W3194985222","https://openalex.org/W2518587255","https://openalex.org/W1968265719"],"abstract_inverted_index":{"Word":[0],"embeddings":[1,35,116],"have":[2,15],"gained":[3],"significant":[4],"attention":[5],"as":[6,82],"learnable":[7],"representations":[8,56],"of":[9,23,39,57,69,98,123,141],"semantic":[10],"relations":[11],"between":[12],"words,":[13],"and":[14,62],"been":[16,31],"shown":[17],"to":[18,33,53],"improve":[19],"upon":[20],"the":[21,37,67,102,110,121,124,145],"results":[22],"traditional":[24,78],"word":[25,79,115],"representations.":[26],"However,":[27],"little":[28],"effort":[29],"has":[30],"devoted":[32],"using":[34],"for":[36,66,88,101,114,129,147],"retrieval":[38],"entity":[40,71],"associations":[41],"beyond":[42],"pairwise":[43],"relations.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48,94,106,132],"use":[49],"popular":[50],"embedding":[51,103,136],"methods":[52,137],"train":[54],"vector":[55],"an":[58],"entity-annotated":[59],"news":[60,74],"corpus,":[61],"evaluate":[63],"their":[64],"performance":[65,122],"task":[68],"predicting":[70],"participation":[72],"in":[73],"events":[75,89],"versus":[76],"a":[77,83,96],"cooccurrence":[80,126],"network":[81],"baseline.":[84],"To":[85],"support":[86],"queries":[87],"with":[90],"multiple":[91],"participating":[92],"entities,":[93,131],"test":[95],"number":[97],"combination":[99,112],"modes":[100,113],"vectors.":[104],"While":[105],"find":[107],"that":[108,134],"even":[109],"best":[111],"do":[117],"not":[118],"quite":[119],"reach":[120],"full":[125],"network,":[127],"especially":[128],"rare":[130],"observe":[133],"different":[135,139],"model":[138],"types":[140],"relations,":[142],"thereby":[143],"indicating":[144],"potential":[146],"ensemble":[148],"methods.":[149]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4288280738","counts_by_year":[],"updated_date":"2024-10-07T20:05:06.063874","created_date":"2022-07-28"}