{"id":"https://openalex.org/W7106255181","doi":"https://doi.org/10.1109/itw62417.2025.11240323","title":"Context-Aware Search and Retrieval Over Erasure Channels","display_name":"Context-Aware Search and Retrieval Over Erasure Channels","publication_year":2025,"publication_date":"2025-09-29","ids":{"openalex":"https://openalex.org/W7106255181","doi":"https://doi.org/10.1109/itw62417.2025.11240323"},"language":null,"primary_location":{"id":"doi:10.1109/itw62417.2025.11240323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw62417.2025.11240323","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Information Theory Workshop (ITW)","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":"Sara Ghasvarianjahromi","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara Ghasvarianjahromi","raw_affiliation_strings":["New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,New Jersey,USA,07102"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,New Jersey,USA,07102","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yauhen Yakimenka","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yauhen Yakimenka","raw_affiliation_strings":["New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,New Jersey,USA,07102"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,New Jersey,USA,07102","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":null,"display_name":"J\u00f6rg Kliewer","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J\u00f6rg Kliewer","raw_affiliation_strings":["New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,New Jersey,USA,07102"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,New Jersey,USA,07102","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64573044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"821","last_page":"826"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.6085000038146973,"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":0.6085000038146973,"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/T11269","display_name":"Algorithms and Data Compression","score":0.05130000039935112,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.03350000083446503,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/redundancy","display_name":"Redundancy (engineering)","score":0.6021999716758728},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.5794000029563904},{"id":"https://openalex.org/keywords/erasure","display_name":"Erasure","score":0.5131999850273132},{"id":"https://openalex.org/keywords/vector-space-model","display_name":"Vector space model","score":0.5047000050544739},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4381999969482422},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.436599999666214},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4169999957084656},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3935999870300293},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3783000111579895},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.36309999227523804}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7617999911308289},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6021999716758728},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.5794000029563904},{"id":"https://openalex.org/C2778790127","wikidata":"https://www.wikidata.org/wiki/Q484885","display_name":"Erasure","level":2,"score":0.5131999850273132},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.5047000050544739},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4381999969482422},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4068000018596649},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4050000011920929},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.35920000076293945},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3465999960899353},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3244999945163727},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C134400042","wikidata":"https://www.wikidata.org/wiki/Q2372244","display_name":"Symbol (formal)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.29010000824928284},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2750999927520752},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2615000009536743},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2590000033378601},{"id":"https://openalex.org/C206468330","wikidata":"https://www.wikidata.org/wiki/Q834373","display_name":"Code rate","level":3,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itw62417.2025.11240323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw62417.2025.11240323","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2029115643","https://openalex.org/W2048176942","https://openalex.org/W2513519930","https://openalex.org/W2796524599","https://openalex.org/W2912924812","https://openalex.org/W2992007572","https://openalex.org/W3198139956","https://openalex.org/W3202895480","https://openalex.org/W4205683915","https://openalex.org/W4249875616","https://openalex.org/W4293149236","https://openalex.org/W4312766166","https://openalex.org/W4317898419","https://openalex.org/W4383753013","https://openalex.org/W4388739236","https://openalex.org/W4399525892","https://openalex.org/W4400526126","https://openalex.org/W4401211953","https://openalex.org/W4401726216","https://openalex.org/W4409132086"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"and":[3,7,99,128],"analyzes":[4],"a":[5,26,33,45,52,57,91],"search":[6],"retrieval":[8,29,110],"model":[9,39],"that":[10,142],"adopts":[11],"key":[12],"semantic":[13],"communication":[14,163],"principles":[15],"from":[16,48],"retrieval-augmented":[17],"generation.":[18],"We":[19],"specifically":[20],"present":[21],"an":[22,61,105],"information-theoretic":[23],"analysis":[24],"of":[25,44,51,69,85,136,157],"remote":[27],"document":[28,121],"system":[30],"operating":[31],"over":[32],"symbol":[34],"erasure":[35],"channel.":[36],"The":[37],"proposed":[38],"encodes":[40],"the":[41,66,70,73,82,86,97,109,114,118,134,137,151,155],"feature":[42,159],"vector":[43],"query,":[46],"derived":[47],"term-frequency":[49],"weights":[50],"language":[53],"corpus":[54],"by":[55],"using":[56],"repetition":[58],"code":[59],"with":[60],"adaptive":[62],"rate":[63],"dependent":[64],"on":[65,81,126],"contextual":[67,83],"importance":[68],"terms.":[71],"At":[72],"decoder,":[74],"we":[75,103],"select":[76],"between":[77],"two":[78],"documents":[79],"based":[80],"closeness":[84],"recovered":[87],"query.":[88],"By":[89],"leveraging":[90],"jointly":[92],"Gaussian":[93],"approximation":[94],"for":[95,108],"both":[96],"true":[98],"reconstructed":[100],"similarity":[101],"scores,":[102],"derive":[104],"explicit":[106],"expression":[107],"error":[111,152],"probability,":[112],"i.e.,":[113],"probability":[115],"under":[116],"which":[117],"less":[119],"similar":[120],"is":[122],"selected.":[123],"Numerical":[124],"simulations":[125],"synthetic":[127],"real-world":[129],"data":[130],"(Google":[131],"NQ)":[132],"confirm":[133],"validity":[135],"analysis.":[138],"They":[139],"further":[140],"demonstrate":[141],"assigning":[143],"greater":[144],"redundancy":[145],"to":[146],"critical":[147],"features":[148],"effectively":[149],"reduces":[150],"rate,":[153],"highlighting":[154],"effectiveness":[156],"semantic-aware":[158],"encoding":[160],"in":[161],"error-prone":[162],"settings.":[164]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-23T00:00:00"}