{"id":"https://openalex.org/W2765161047","doi":"https://doi.org/10.1109/tbdata.2017.2763164","title":"Knowledge Graphs for Social Good: An Entity-Centric Search Engine for the Human Trafficking Domain","display_name":"Knowledge Graphs for Social Good: An Entity-Centric Search Engine for the Human Trafficking Domain","publication_year":2017,"publication_date":"2017-10-19","ids":{"openalex":"https://openalex.org/W2765161047","doi":"https://doi.org/10.1109/tbdata.2017.2763164","mag":"2765161047"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2017.2763164","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2017.2763164","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-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/A5074197492","display_name":"Mayank Kejriwal","orcid":"https://orcid.org/0000-0001-5988-8305"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mayank Kejriwal","raw_affiliation_strings":["USC Viterbi School of Engineering, Information Sciences Institute, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"USC Viterbi School of Engineering, Information Sciences Institute, Los Angeles, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068184256","display_name":"Pedro Szekely","orcid":"https://orcid.org/0000-0002-4621-2266"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pedro Szekely","raw_affiliation_strings":["USC Viterbi School of Engineering, Information Sciences Institute, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"USC Viterbi School of Engineering, Information Sciences Institute, Los Angeles, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074197492"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.5762,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.96916495,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"8","issue":"3","first_page":"592","last_page":"606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9980999827384949,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9980999827384949,"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":0.9939000010490417,"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/T11719","display_name":"Data Quality and Management","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8655169010162354},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6645469069480896},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.6140421628952026},{"id":"https://openalex.org/keywords/terabyte","display_name":"Terabyte","score":0.5720553994178772},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.532055675983429},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5254920125007629},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5184975862503052},{"id":"https://openalex.org/keywords/semantic-search","display_name":"Semantic search","score":0.5088591575622559},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5032405257225037},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4907163381576538},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.41259926557540894},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36221760511398315},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.13576126098632812},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.09036493301391602}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8655169010162354},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6645469069480896},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.6140421628952026},{"id":"https://openalex.org/C199683683","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Terabyte","level":2,"score":0.5720553994178772},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.532055675983429},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5254920125007629},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5184975862503052},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.5088591575622559},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5032405257225037},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4907163381576538},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.41259926557540894},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36221760511398315},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.13576126098632812},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.09036493301391602},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2017.2763164","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2017.2763164","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.49000000953674316,"display_name":"Gender equality"},{"id":"https://metadata.un.org/sdg/8","score":0.4099999964237213,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G5171659921","display_name":null,"funder_award_id":"FA8750- 14-C-0240","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W102708294","https://openalex.org/W216536535","https://openalex.org/W651225892","https://openalex.org/W790941020","https://openalex.org/W1540048718","https://openalex.org/W1553019137","https://openalex.org/W1580314469","https://openalex.org/W1870305865","https://openalex.org/W1942169943","https://openalex.org/W1964162497","https://openalex.org/W1972336145","https://openalex.org/W1981791873","https://openalex.org/W1992673035","https://openalex.org/W2016753842","https://openalex.org/W2022760666","https://openalex.org/W2024791376","https://openalex.org/W2026205964","https://openalex.org/W2031158656","https://openalex.org/W2037802158","https://openalex.org/W2038949047","https://openalex.org/W2049711652","https://openalex.org/W2074922014","https://openalex.org/W2081580037","https://openalex.org/W2094728533","https://openalex.org/W2097453652","https://openalex.org/W2103296194","https://openalex.org/W2106950427","https://openalex.org/W2110367654","https://openalex.org/W2115770258","https://openalex.org/W2127978399","https://openalex.org/W2131448664","https://openalex.org/W2132874238","https://openalex.org/W2134145495","https://openalex.org/W2134150392","https://openalex.org/W2139646386","https://openalex.org/W2149692139","https://openalex.org/W2153267064","https://openalex.org/W2168044903","https://openalex.org/W2222863356","https://openalex.org/W2231151070","https://openalex.org/W2242459625","https://openalex.org/W2293480675","https://openalex.org/W2494071875","https://openalex.org/W2605217525","https://openalex.org/W2606000258","https://openalex.org/W2963694862","https://openalex.org/W3103423064","https://openalex.org/W3146259567","https://openalex.org/W4251372957","https://openalex.org/W4252157188","https://openalex.org/W4298078389","https://openalex.org/W6608754186","https://openalex.org/W6622627872","https://openalex.org/W6629638141","https://openalex.org/W6632374713","https://openalex.org/W6633154970","https://openalex.org/W6678039958","https://openalex.org/W6683209587","https://openalex.org/W6683226453","https://openalex.org/W6687322159"],"related_works":["https://openalex.org/W2359166167","https://openalex.org/W2772359885","https://openalex.org/W3590553","https://openalex.org/W3110844189","https://openalex.org/W2899331914","https://openalex.org/W3011471740","https://openalex.org/W1976839151","https://openalex.org/W2336826532","https://openalex.org/W3040185272","https://openalex.org/W2373953901"],"abstract_inverted_index":{"Web":[0,22],"advertising":[1],"related":[2],"to":[3,24,56,91,101,144,164],"Human":[4],"Trafficking":[5],"(HT)":[6],"activity":[7],"has":[8],"been":[9,173],"on":[10,112,130,136,151],"the":[11,28,63,79,109,154,169],"rise":[12],"in":[13,27,51,62],"recent":[14,44],"years.":[15],"Answering":[16],"entity-centric":[17,45],"questions":[18,135],"over":[19,117],"crawled":[20,77],"HT":[21,64,127],"corpora":[23],"assist":[25,57],"investigators":[26,90],"real":[29],"world":[30],"is":[31],"an":[32,84],"important":[33],"social":[34],"problem,":[35],"involving":[36],"many":[37],"technical":[38],"challenges.":[39],"This":[40],"paper":[41],"describes":[42],"a":[43,52,72,102,120,137,148],"knowledge":[46,86],"graph":[47],"effort":[48],"that":[49],"resulted":[50],"semantic":[53,104],"search":[54,99,110],"engine":[55,111],"analysts":[58],"and":[59,88,162],"investigative":[60,98],"experts":[61],"domain.":[65],"The":[66,157],"overall":[67],"approach":[68,150],"takes":[69],"as":[70],"input":[71],"large":[73],"corpus":[74],"of":[75,123,134,153,168],"advertisements":[76],"from":[78,116],"Web,":[80],"structures":[81],"it":[82],"into":[83],"indexed":[85],"graph,":[87],"enables":[89],"satisfy":[92],"their":[93],"information":[94],"needs":[95],"by":[96],"posing":[97],"queries":[100],"special-purpose":[103],"execution":[105],"engine.":[106],"We":[107],"evaluated":[108],"real-world":[113],"data":[114],"collected":[115],"90,000":[118],"webpages,":[119],"significant":[121],"fraction":[122],"which":[124],"correlates":[125],"with":[126,176],"activity.":[128],"Performance":[129],"four":[131,155],"relevant":[132],"categories":[133],"mean":[138],"average":[139],"precision":[140],"metric":[141],"were":[142],"found":[143],"be":[145],"promising,":[146],"outperforming":[147],"learning-to-rank":[149],"three":[152],"categories.":[156],"prototype":[158,170],"uses":[159],"open-source":[160],"components":[161],"scales":[163],"terabyte-scale":[165],"corpora.":[166],"Principles":[167],"have":[171],"also":[172],"independently":[174],"replicated,":[175],"similarly":[177],"successful":[178],"results.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
