{"id":"https://openalex.org/W4414243996","doi":"https://doi.org/10.3390/e27090961","title":"SE-MSLC: Semantic Entropy-Driven Keyword Analysis and Multi-Stage Logical Combination Recall for Search Engine","display_name":"SE-MSLC: Semantic Entropy-Driven Keyword Analysis and Multi-Stage Logical Combination Recall for Search Engine","publication_year":2025,"publication_date":"2025-09-16","ids":{"openalex":"https://openalex.org/W4414243996","doi":"https://doi.org/10.3390/e27090961","pmid":"https://pubmed.ncbi.nlm.nih.gov/41008088"},"language":"en","primary_location":{"id":"doi:10.3390/e27090961","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27090961","pdf_url":"https://www.mdpi.com/1099-4300/27/9/961/pdf?version=1758019134","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/27/9/961/pdf?version=1758019134","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068904286","display_name":"Hai\u2010Hua Lu","orcid":"https://orcid.org/0000-0003-3604-7145"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haihua Lu","raw_affiliation_strings":["School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101768523","display_name":"Liang Yu","orcid":"https://orcid.org/0000-0002-3388-7790"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liang Yu","raw_affiliation_strings":["AIoT Edge Computing Engineering Technology Research Center of Dongguan City, Guangdong University of Science and Technology, Dongguan 523083, China","Guangdong AIoT Application Innovation Joint Laboratory, Guangdong University of Science and Technology, Dongguan 523083, China","School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China"],"raw_orcid":"https://orcid.org/0000-0002-3388-7790","affiliations":[{"raw_affiliation_string":"AIoT Edge Computing Engineering Technology Research Center of Dongguan City, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"Guangdong AIoT Application Innovation Joint Laboratory, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014553224","display_name":"Yantao He","orcid":"https://orcid.org/0000-0002-4875-224X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yantao He","raw_affiliation_strings":["School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102633358","display_name":"Liwei Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liwei Tian","raw_affiliation_strings":["AIoT Edge Computing Engineering Technology Research Center of Dongguan City, Guangdong University of Science and Technology, Dongguan 523083, China","School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AIoT Edge Computing Engineering Technology Research Center of Dongguan City, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Computer Science, Guangdong University of Science and Technology, Dongguan 523083, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101768523"],"corresponding_institution_ids":["https://openalex.org/I2799850029"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":1.9753,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.89830954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"27","issue":"9","first_page":"961","last_page":"961"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9937000274658203,"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":0.9937000274658203,"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":0.9904000163078308,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9897000193595886,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/concept-search","display_name":"Concept search","score":0.6970999836921692},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6955999732017517},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.6532999873161316},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.6434000134468079},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5476999878883362},{"id":"https://openalex.org/keywords/semantic-search","display_name":"Semantic search","score":0.5080000162124634},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.45730000734329224},{"id":"https://openalex.org/keywords/inverted-index","display_name":"Inverted index","score":0.45500001311302185},{"id":"https://openalex.org/keywords/search-oriented-architecture","display_name":"Search-oriented architecture","score":0.4408000111579895},{"id":"https://openalex.org/keywords/human\u2013computer-information-retrieval","display_name":"Human\u2013computer information retrieval","score":0.41999998688697815}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8555999994277954},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.7181000113487244},{"id":"https://openalex.org/C182861755","wikidata":"https://www.wikidata.org/wiki/Q5158391","display_name":"Concept search","level":4,"score":0.6970999836921692},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6955999732017517},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.6532999873161316},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.6434000134468079},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5476999878883362},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.5080000162124634},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C130590232","wikidata":"https://www.wikidata.org/wiki/Q1671754","display_name":"Inverted index","level":3,"score":0.45500001311302185},{"id":"https://openalex.org/C157154645","wikidata":"https://www.wikidata.org/wiki/Q7441612","display_name":"Search-oriented architecture","level":5,"score":0.4408000111579895},{"id":"https://openalex.org/C90288658","wikidata":"https://www.wikidata.org/wiki/Q3318149","display_name":"Human\u2013computer information retrieval","level":3,"score":0.41999998688697815},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.3878999948501587},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35760000348091125},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.3555999994277954},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.32019999623298645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31839999556541443},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C21025794","wikidata":"https://www.wikidata.org/wiki/Q5141219","display_name":"Cognitive models of information retrieval","level":4,"score":0.30959999561309814},{"id":"https://openalex.org/C173862523","wikidata":"https://www.wikidata.org/wiki/Q5421270","display_name":"Explicit semantic analysis","level":5,"score":0.2906000018119812},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.28189998865127563},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C14838553","wikidata":"https://www.wikidata.org/wiki/Q7441639","display_name":"Search analytics","level":4,"score":0.27619999647140503},{"id":"https://openalex.org/C20228898","wikidata":"https://www.wikidata.org/wiki/Q83540","display_name":"Full text search","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C19889080","wikidata":"https://www.wikidata.org/wiki/Q2835852","display_name":"Beam search","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.2680000066757202},{"id":"https://openalex.org/C2778816267","wikidata":"https://www.wikidata.org/wiki/Q21015578","display_name":"Semantic query","level":4,"score":0.26330000162124634},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C2778698081","wikidata":"https://www.wikidata.org/wiki/Q179797","display_name":"Thesaurus","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C22639730","wikidata":"https://www.wikidata.org/wiki/Q7702546","display_name":"Term Discrimination","level":5,"score":0.2533000111579895}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e27090961","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27090961","pdf_url":"https://www.mdpi.com/1099-4300/27/9/961/pdf?version=1758019134","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:41008088","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41008088","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:e116803243ba46f68c1b4a33b6aba67d","is_oa":true,"landing_page_url":"https://doaj.org/article/e116803243ba46f68c1b4a33b6aba67d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 27, Iss 9, p 961 (2025)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:11277071","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12468705","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:12468705","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12468705/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e27090961","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27090961","pdf_url":"https://www.mdpi.com/1099-4300/27/9/961/pdf?version=1758019134","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414243996.pdf","grobid_xml":"https://content.openalex.org/works/W4414243996.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2043909051","https://openalex.org/W2047221353","https://openalex.org/W2049870103","https://openalex.org/W2051497960","https://openalex.org/W2085030399","https://openalex.org/W2147717514","https://openalex.org/W2154851992","https://openalex.org/W2250539671","https://openalex.org/W2512971201","https://openalex.org/W2962756421","https://openalex.org/W3027879771","https://openalex.org/W3034912391","https://openalex.org/W3036320503","https://openalex.org/W3098468692","https://openalex.org/W3099700870","https://openalex.org/W3104097132","https://openalex.org/W3109479953","https://openalex.org/W3112768174","https://openalex.org/W3179467154","https://openalex.org/W3209048533","https://openalex.org/W4213009331","https://openalex.org/W4240422607","https://openalex.org/W4306317050","https://openalex.org/W4384625684","https://openalex.org/W4385637535","https://openalex.org/W4387848542","https://openalex.org/W4396821195","https://openalex.org/W4407478418","https://openalex.org/W4412377187","https://openalex.org/W4412394903"],"related_works":[],"abstract_inverted_index":{"Information":[0],"retrieval":[1,27,37,46,165,187,194],"serves":[2],"as":[3],"a":[4,57,111,117,121],"critical":[5],"methodology":[6],"for":[7],"accurately":[8],"and":[9,82,120,150,155,167,189,209,225],"efficiently":[10],"obtaining":[11],"the":[12,36,66,76,79,83,89,95,127,133,137,142,145,153,160,171,179,183,186,190,193,197,206,216,220,226,234],"required":[13],"information":[14,26,32,175],"from":[15,136],"massive":[16],"amounts":[17],"of":[18,39,78,85,97,141,147,185,192],"data.":[19],"In":[20],"this":[21],"paper,":[22],"we":[23,55,109,200],"propose":[24,56,110],"an":[25],"framework":[28],"(SE-MSLC)":[29],"that":[30,115,215],"utilizes":[31],"theory":[33,84],"to":[34,92,104,170,196],"improve":[35],"effectiveness":[38],"inverted":[40],"index":[41],"retrieval,":[42],"thus":[43],"achieving":[44],"higher-quality":[45],"results":[47,188,195,213],"in":[48,65,126,144,237],"intelligent":[49],"vertical":[50,239],"domain":[51,240],"search":[52,73,80,90,241],"engines.":[53],"First,":[54],"semantic":[58,86],"entropy-driven":[59],"keyword":[60],"importance":[61],"analysis":[62],"method":[63,71,218],"(SE-KIA)":[64],"query":[67,74,98,143],"understanding":[68],"module.":[69,129],"This":[70],"combines":[72,116],"logs,":[75],"corpus":[77],"engine,":[81],"entropy,":[87],"enabling":[88],"engine":[91],"dynamically":[93],"adjust":[94],"weights":[96],"keywords,":[99],"thereby":[100],"improving":[101],"its":[102],"ability":[103],"recognize":[105],"user":[106],"intent.":[107],"Then,":[108],"hybrid":[112],"recall":[113,128,149],"strategy":[114,119,124],"multi-stage":[118],"logical":[122,157],"combination":[123],"(HRS-MSLC)":[125],"It":[130],"separately":[131],"recalls":[132],"keywords":[134,172],"obtained":[135],"multi-granularity":[138],"word":[139],"segmentation":[140],"form":[146],"multi-queue":[148],"simultaneously":[151],"considers":[152],"\"AND\"":[154],"\"OR\"":[156],"relationships":[158],"between":[159,182],"keywords.":[161],"By":[162],"systematically":[163],"managing":[164],"uncertainty":[166],"giving":[168],"priority":[169],"with":[173],"high":[174],"content,":[176],"it":[177],"achieves":[178],"best":[180],"balance":[181],"quantity":[184],"relevance":[191],"query.":[198],"Finally,":[199],"experimentally":[201],"evaluate":[202],"our":[203,238],"methods":[204],"using":[205],"Hit":[207,221,227],"Rate@K":[208],"case":[210],"analysis.":[211],"Our":[212],"demonstrate":[214],"proposed":[217],"improves":[219],"Rate@1":[222],"by":[223,229],"7.3%":[224],"Rate@3":[228],"6.6%":[230],"while":[231],"effectively":[232],"solving":[233],"bad":[235],"cases":[236],"engine.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}