{"id":"https://openalex.org/W4417282618","doi":"https://doi.org/10.1109/pimrc62392.2025.11274592","title":"Learning the Underlying Semantic Model Using Multi-Sensor Observations for Goal-Oriented Semantic Communications","display_name":"Learning the Underlying Semantic Model Using Multi-Sensor Observations for Goal-Oriented Semantic Communications","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4417282618","doi":"https://doi.org/10.1109/pimrc62392.2025.11274592"},"language":null,"primary_location":{"id":"doi:10.1109/pimrc62392.2025.11274592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc62392.2025.11274592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-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":null,"display_name":"M. Ilyas Caliskan","orcid":null},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"M. Ilyas Caliskan","raw_affiliation_strings":["Bilkent University,Dept. of Electrical and Electronics Engineering,Ankara,Turkey"],"affiliations":[{"raw_affiliation_string":"Bilkent University,Dept. of Electrical and Electronics Engineering,Ankara,Turkey","institution_ids":["https://openalex.org/I168864056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048023330","display_name":"Tolga M. Duman","orcid":"https://orcid.org/0000-0002-5187-8660"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Tolga M. Duman","raw_affiliation_strings":["Bilkent University,Dept. of Electrical and Electronics Engineering,Ankara,Turkey"],"affiliations":[{"raw_affiliation_string":"Bilkent University,Dept. of Electrical and Electronics Engineering,Ankara,Turkey","institution_ids":["https://openalex.org/I168864056"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065341937","display_name":"Orhan Ar\u0131kan","orcid":"https://orcid.org/0000-0002-3698-8888"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Orhan Ar\u0131kan","raw_affiliation_strings":["Bilkent University,Dept. of Electrical and Electronics Engineering,Ankara,Turkey"],"affiliations":[{"raw_affiliation_string":"Bilkent University,Dept. of Electrical and Electronics Engineering,Ankara,Turkey","institution_ids":["https://openalex.org/I168864056"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I168864056"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21461291,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.8795999884605408,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.8795999884605408,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.006899999920278788,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13553","display_name":"Age of Information Optimization","score":0.006800000090152025,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/semantic-computing","display_name":"Semantic computing","score":0.49880000948905945},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4902999997138977},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4794999957084656},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.4422000050544739},{"id":"https://openalex.org/keywords/semantic-memory","display_name":"Semantic memory","score":0.44209998846054077},{"id":"https://openalex.org/keywords/semantic-network","display_name":"Semantic network","score":0.43309998512268066},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4325000047683716},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4133000075817108},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.3643999993801117}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8317000269889832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.608299970626831},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.49880000948905945},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4902999997138977},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48399999737739563},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.44209998846054077},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C103692084","wikidata":"https://www.wikidata.org/wiki/Q1765824","display_name":"Semantic grid","level":3,"score":0.3361999988555908},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.304500013589859},{"id":"https://openalex.org/C158156997","wikidata":"https://www.wikidata.org/wiki/Q1416645","display_name":"Models of communication","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.28700000047683716},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C6881194","wikidata":"https://www.wikidata.org/wiki/Q7449091","display_name":"Semantic technology","level":4,"score":0.2854999899864197},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.2603999972343445},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2572000026702881},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc62392.2025.11274592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc62392.2025.11274592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2076618452","https://openalex.org/W2125344207","https://openalex.org/W2981096252","https://openalex.org/W3110989801","https://openalex.org/W3167080497","https://openalex.org/W4247319331","https://openalex.org/W4312051246","https://openalex.org/W4322576964","https://openalex.org/W4400612464"],"related_works":[],"abstract_inverted_index":{"Goal-oriented":[0],"semantic":[1,41,56,85,97,116],"communications":[2,86],"and":[3,26,43,70,87,103,124],"signal":[4],"processing":[5],"are":[6],"foreseen":[7],"to":[8,76,93],"play":[9],"a":[10,62],"key":[11],"role":[12],"in":[13,21],"advancing":[14],"future":[15],"communication":[16],"networks.":[17],"Leveraging":[18],"recent":[19],"advances":[20],"machine":[22],"learning":[23],"(ML)":[24],"techniques":[25],"artificial":[27],"intelligence":[28],"(AI),":[29],"research":[30],"is":[31],"shifting":[32],"towards":[33],"intelligent":[34],"end-to-end":[35],"systems":[36],"that":[37,52,110],"can":[38,58],"extract":[39],"relevant":[40],"information":[42,57],"transmit":[44],"only":[45],"when":[46],"necessary.":[47],"It":[48],"was":[49],"recently":[50],"proposed":[51,112],"graph":[53],"languages":[54],"representing":[55],"be":[59],"modeled":[60],"using":[61],"hidden":[63],"semi-Markov":[64],"model":[65,98,117],"(HSMM)":[66],"for":[67,82],"smoothing,":[68],"learning,":[69],"fusion":[71],"algorithms.":[72],"This":[73],"paper":[74],"aims":[75],"build":[77],"upon":[78],"this":[79],"HSMM":[80],"framework":[81],"multi-sensor":[83,101],"goal-oriented":[84],"proposes":[88],"an":[89],"expectation-maximization":[90],"(EM)":[91],"algorithm":[92,113],"learn":[94],"the":[95,111,115,120,127],"underlying":[96],"by":[99,118],"incorporating":[100],"observations":[102,123],"handling":[104],"missing":[105,130],"data.":[106],"The":[107],"results":[108],"show":[109],"learns":[114],"utilizing":[119],"set":[121],"of":[122,129],"effectively":[125],"mitigates":[126],"effects":[128],"observations.":[131]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-12-12T00:00:00"}