{"id":"https://openalex.org/W3046438426","doi":"https://doi.org/10.1145/3383583.3398563","title":"Temporal Summarization of Scholarly Paper Collections by Semantic Change Estimation: Case Study of CORD-19 Dataset","display_name":"Temporal Summarization of Scholarly Paper Collections by Semantic Change Estimation: Case Study of CORD-19 Dataset","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3046438426","doi":"https://doi.org/10.1145/3383583.3398563","mag":"3046438426"},"language":"en","primary_location":{"id":"doi:10.1145/3383583.3398563","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383583.3398563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020","raw_type":"proceedings-article"},"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/A5023268855","display_name":"Muhammad Syafiq Mohd Pozi","orcid":"https://orcid.org/0000-0001-9379-7351"},"institutions":[{"id":"https://openalex.org/I94625822","display_name":"Northern University of Malaysia","ror":"https://ror.org/01ss10648","country_code":"MY","type":"education","lineage":["https://openalex.org/I94625822"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Muhammad Syafiq Mohd Pozi","raw_affiliation_strings":["Universiti Utara Malaysia, Kedah, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universiti Utara Malaysia, Kedah, Malaysia","institution_ids":["https://openalex.org/I94625822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079733597","display_name":"Adam Jatowt","orcid":"https://orcid.org/0000-0001-7235-0665"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Adam Jatowt","raw_affiliation_strings":["Kyoto University, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055074100","display_name":"Yukiko Kawai","orcid":"https://orcid.org/0000-0003-2627-6673"},"institutions":[{"id":"https://openalex.org/I168356945","display_name":"Kyoto Sangyo University","ror":"https://ror.org/05t70xh16","country_code":"JP","type":"education","lineage":["https://openalex.org/I168356945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yukiko Kawai","raw_affiliation_strings":["Kyoto Sangyo University, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyoto Sangyo University, Kyoto, Japan","institution_ids":["https://openalex.org/I168356945"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4609,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64407607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"459","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9922999739646912,"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":0.9922999739646912,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9757999777793884,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/automatic-summarization","display_name":"Automatic summarization","score":0.9045709371566772},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6786187887191772},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5240721106529236},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5057134628295898},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.48734769225120544},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47454628348350525},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4611227214336395},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.429545521736145},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3440481722354889}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9045709371566772},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6786187887191772},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5240721106529236},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5057134628295898},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.48734769225120544},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47454628348350525},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4611227214336395},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.429545521736145},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3440481722354889},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383583.3398563","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383583.3398563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G5729551652","display_name":null,"funder_award_id":"FRGS-RACER/1/2019/SS09/UUM//2","funder_id":"https://openalex.org/F4320321709","funder_display_name":"Ministry of Higher Education, Malaysia"}],"funders":[{"id":"https://openalex.org/F4320321709","display_name":"Ministry of Higher Education, Malaysia","ror":"https://ror.org/05mcs2t73"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1836521361","https://openalex.org/W2101074118","https://openalex.org/W2102343050","https://openalex.org/W2153579005","https://openalex.org/W2187089797"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W1517524280"],"abstract_inverted_index":{"The":[0],"new":[1],"pandemic":[2],"disease":[3],"caused":[4],"by":[5],"COVID-19":[6],"virus":[7],"is":[8],"the":[9,13,16],"crucial":[10],"event":[11],"over":[12,61],"world":[14],"in":[15],"beginning":[17],"of":[18,55,70,74],"2020.":[19],"Studies":[20],"on":[21,37],"corona":[22],"viruses":[23],"have":[24],"been":[25],"however":[26],"carried":[27],"since":[28],"several":[29],"decades":[30],"ago,":[31],"with":[32],"recent":[33],"research":[34],"papers":[35],"published":[36],"weekly":[38],"basis.":[39],"We":[40],"demonstrate":[41],"a":[42,51],"simple":[43],"approach":[44],"to":[45,49,66,88],"explore":[46],"CORD-19":[47],"dataset":[48],"provide":[50],"high":[52],"level":[53],"overview":[54],"important":[56],"semantic":[57],"changes":[58],"that":[59,77],"occurred":[60],"time.":[62],"Our":[63],"method":[64],"aims":[65],"support":[67],"better":[68],"understanding":[69],"large":[71],"domain-specific":[72],"collections":[73],"scholarly":[75],"publications":[76],"span":[78],"long":[79],"time":[80],"periods":[81],"and":[82],"could":[83],"be":[84],"regarded":[85],"as":[86],"complementary":[87],"frequency-based":[89],"analysis.":[90]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}
