{"id":"https://openalex.org/W2003299095","doi":"https://doi.org/10.1109/bigdata.2014.7004310","title":"Crowdsourced query augmentation through semantic discovery of domain-specific jargon","display_name":"Crowdsourced query augmentation through semantic discovery of domain-specific jargon","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2003299095","doi":"https://doi.org/10.1109/bigdata.2014.7004310","mag":"2003299095"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004310","doi":"https://doi.org/10.1109/bigdata.2014.7004310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004310","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"IEEE International Conference on Big Data (BigData)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"volume":null,"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/A5011311827","display_name":"Khalifeh AlJadda","orcid":"https://orcid.org/0000-0002-4133-2883","observed_orcids":["https://orcid.org/0000-0002-4133-2883"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khalifeh AlJadda","raw_affiliation_strings":["Department of Computer Science, University of Georgia, Athens, Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Georgia, Athens, Georgia","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030822548","display_name":"Mohammed Korayem","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]},{"id":"https://openalex.org/I592451","display_name":"Indiana University","ror":"https://ror.org/01kg8sb98","country_code":"US","type":"education","lineage":["https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammed Korayem","raw_affiliation_strings":["School of Informatics & Computing, Indiana University, Bloomington, Indiana"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics & Computing, Indiana University, Bloomington, Indiana","institution_ids":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070636413","display_name":"Trey Grainger","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trey Grainger","raw_affiliation_strings":["Director of Engineering, CareerBuilder Search Group, Norcross, Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Director of Engineering, CareerBuilder Search Group, Norcross, Georgia","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chris Russell","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chris Russell","raw_affiliation_strings":["Engineering Lead, Relevancy CareerBuilder Search Group, Norcross, Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Engineering Lead, Relevancy CareerBuilder Search Group, Norcross, Georgia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1285,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.92118054,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"808","last_page":"815"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9603999853134155,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9603999853134155,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.01269999984651804,"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":0.00430000014603138,"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/query-expansion","display_name":"query expansion","score":0.9269999861717224},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"crowdsourcing","score":0.7210000157356262},{"id":"https://openalex.org/keywords/semantic-relations","display_name":"semantic relations","score":0.5289999842643738},{"id":"https://openalex.org/keywords/semantic-search","display_name":"semantic search","score":0.5509999990463257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.869131326675415},{"id":"https://openalex.org/C2777611551","wikidata":"https://www.wikidata.org/wiki/Q17951","display_name":"Jargon","level":2,"score":0.6969621181488037},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.655510425567627},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.6541723012924194},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5288259387016296},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.49149930477142334},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.47068125009536743},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.445738285779953},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4376378357410431},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4211651384830475},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3978118300437927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35925066471099854},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3345714211463928},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.24206843972206116},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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:10.1109/bigdata.2014.7004310","doi":"https://doi.org/10.1109/bigdata.2014.7004310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004310","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"IEEE International Conference on Big Data (BigData)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6299999952316284}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W872435579","https://openalex.org/W1567365482","https://openalex.org/W1977789176","https://openalex.org/W1994765180","https://openalex.org/W2033952804","https://openalex.org/W2042281163","https://openalex.org/W2081580037","https://openalex.org/W2101746535","https://openalex.org/W2109070285","https://openalex.org/W2110086534","https://openalex.org/W2119738171","https://openalex.org/W2147152072","https://openalex.org/W2173213060","https://openalex.org/W2480620222","https://openalex.org/W2803437449"],"related_works":["https://openalex.org/W2751183094","https://openalex.org/W1562855630","https://openalex.org/W2165084432","https://openalex.org/W2086378526","https://openalex.org/W2594222840","https://openalex.org/W2902039763","https://openalex.org/W2403516839","https://openalex.org/W7097599793","https://openalex.org/W2295393218","https://openalex.org/W3208229871"],"abstract_inverted_index":{"Most":[0],"work":[1],"in":[2,108],"semantic":[3,28,86,103],"search":[4,89,99],"has":[5],"thus":[6],"far":[7],"focused":[8],"upon":[9,16],"either":[10],"manually":[11],"building":[12],"language-specific":[13],"taxonomies/ontologies":[14],"or":[15,22,64],"automatic":[17],"techniques":[18],"such":[19],"as":[20],"clustering":[21],"dimensionality":[23],"reduction":[24],"to":[25,46,53,62,65,101],"discover":[26,102],"latent":[27,85],"links":[29,73],"within":[30],"the":[31,49,72],"content":[32],"that":[33,71,111],"is":[34,39,44,51,94,112],"being":[35],"searched.":[36],"The":[37,91],"former":[38],"very":[40],"labor":[41],"intensive":[42],"and":[43,55,117],"hard":[45,58],"maintain,":[47],"while":[48],"latter":[50],"prone":[52],"noise":[54],"may":[56],"be":[57],"for":[59,83],"a":[60,79,109],"human":[61,115],"understand":[63],"interact":[66],"with":[67],"directly.":[68],"We":[69],"believe":[70],"between":[74,88,105],"similar":[75],"user's":[76],"queries":[77],"represent":[78],"largely":[80],"untapped":[81],"source":[82],"discovering":[84],"relationships":[87,104],"terms.":[90],"proposed":[92],"system":[93],"capable":[95],"of":[96],"mining":[97],"user":[98],"logs":[100],"key":[106],"phrases":[107],"manner":[110],"language":[113],"agnostic,":[114],"understandable,":[116],"virtually":[118],"noise-free.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}
