{"id":"https://openalex.org/W2797724060","doi":"https://doi.org/10.1145/3178876.3185997","title":"Time Expression Recognition Using a Constituent-based Tagging Scheme","display_name":"Time Expression Recognition Using a Constituent-based Tagging Scheme","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2797724060","doi":"https://doi.org/10.1145/3178876.3185997","mag":"2797724060"},"language":"en","primary_location":{"id":"doi:10.1145/3178876.3185997","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3185997","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3178876.3185997","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002511102","display_name":"Xiaoshi Zhong","orcid":"https://orcid.org/0000-0002-6108-272X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Xiaoshi Zhong","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752356","display_name":"Erik Cambria","orcid":"https://orcid.org/0000-0002-3030-1280"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Erik Cambria","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002511102"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":4.6728,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.95567454,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"983","last_page":"992"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":"Topic Modeling","score":0.9993000030517578,"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":"Natural Language Processing Techniques","score":0.9991999864578247,"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":"Advanced Text Analysis Techniques","score":0.9990000128746033,"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/security-token","display_name":"Security token","score":0.8315388560295105},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.8153690695762634},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7800987958908081},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.6954560279846191},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.6173909902572632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5736870169639587},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5514479875564575},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43855366110801697},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3355560302734375},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3229343295097351},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12331423163414001}],"concepts":[{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.8315388560295105},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.8153690695762634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7800987958908081},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.6954560279846191},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.6173909902572632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5736870169639587},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5514479875564575},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43855366110801697},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3355560302734375},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3229343295097351},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12331423163414001},{"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/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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3178876.3185997","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3185997","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3178876.3185997","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3185997","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W30314283","https://openalex.org/W93363620","https://openalex.org/W131482884","https://openalex.org/W1568155371","https://openalex.org/W1619424147","https://openalex.org/W1893213668","https://openalex.org/W1956885672","https://openalex.org/W1978672522","https://openalex.org/W1990886313","https://openalex.org/W2004763266","https://openalex.org/W2008830554","https://openalex.org/W2039297031","https://openalex.org/W2056451646","https://openalex.org/W2057720927","https://openalex.org/W2096186751","https://openalex.org/W2096953947","https://openalex.org/W2138623081","https://openalex.org/W2144578941","https://openalex.org/W2147489532","https://openalex.org/W2147880316","https://openalex.org/W2147923392","https://openalex.org/W2157275230","https://openalex.org/W2250727448","https://openalex.org/W2250767920","https://openalex.org/W2250936343","https://openalex.org/W2251022776","https://openalex.org/W2251220668","https://openalex.org/W2251559320","https://openalex.org/W2251758222","https://openalex.org/W2251873637","https://openalex.org/W2252277549","https://openalex.org/W2293452551","https://openalex.org/W2295030615","https://openalex.org/W2295415819","https://openalex.org/W2296283641","https://openalex.org/W2308131898","https://openalex.org/W2468432491","https://openalex.org/W2520117834","https://openalex.org/W2739826982","https://openalex.org/W2740006839","https://openalex.org/W2917019145","https://openalex.org/W2950065133","https://openalex.org/W2963625095","https://openalex.org/W2964266863"],"related_works":["https://openalex.org/W2375389409","https://openalex.org/W2961085424","https://openalex.org/W2947903144","https://openalex.org/W2126384842","https://openalex.org/W2547852346","https://openalex.org/W2068018629","https://openalex.org/W3194268462","https://openalex.org/W2034357144","https://openalex.org/W2406849952","https://openalex.org/W2806278276"],"abstract_inverted_index":{"We":[0],"find":[1],"from":[2,25],"four":[3,53],"datasets":[4],"that":[5,109,126],"time":[6,19,23,41,63,78,157],"expressions":[7,24],"are":[8],"formed":[9],"by":[10,112],"loose":[11],"structure":[12],"and":[13,73,121,139,160],"the":[14,60,74,103,113],"words":[15,75],"used":[16],"to":[17,32,39],"express":[18],"information":[20],"can":[21,148],"differentiate":[22],"common":[26],"text.":[27],"The":[28],"findings":[29],"drive":[30],"us":[31],"design":[33],"a":[34,45,84,87],"learning":[35],"method":[36],"named":[37,49,161],"TOMN":[38,43,50,82,88,100,127],"model":[40],"expressions.":[42],"defines":[44],"time-related":[46],"tagging":[47,116],"scheme":[48,51,101,120],"with":[52,86,94],"tags,":[54],"namely":[55,65],"\\tomnT,\\tomnO,":[56],"\\tomnM,and":[57],"\\tomnN,":[58],"indicating":[59],"constituents":[61],"of":[62,105],"expression,":[64],"\\tomnT":[66],"ime":[67],"token,":[68],"\\tomnM":[69],"odifier,":[70],"\\tomnN":[71],"umeral,":[72],"\\tomnO":[76],"utside":[77],"expression.":[79],"In":[80],"modeling,":[81],"assigns":[83],"word":[85],"tag":[89,107],"under":[90],"conditional":[91],"random":[92],"fields":[93],"minimal":[95],"features.":[96],"Essentially,":[97],"our":[98,146],"constituent-based":[99],"overcomes":[102],"problem":[104],"inconsistent":[106],"assignment":[108],"is":[110,128],"caused":[111],"conventional":[114],"position-based":[115],"schemes":[117],"(\\eg":[118],"BIO":[119],"BILOU":[122],"scheme).":[123],"Experiments":[124],"show":[125],"equally":[129],"or":[130],"more":[131,141],"effective":[132],"than":[133],"state-of-the-art":[134],"methods":[135],"on":[136,143],"various":[137],"datasets,":[138],"much":[140],"robust":[142],"cross-datasets.":[144],"Moreover,":[145],"analysis":[147],"explain":[149],"many":[150],"empirical":[151],"observations":[152],"in":[153],"other":[154],"works":[155],"about":[156],"expression":[158],"recognition":[159],"entity":[162],"recognition.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}