{"id":"https://openalex.org/W4384643695","doi":"https://doi.org/10.1145/3539618.3591793","title":"Resilient Retrieval Models for Large Collection","display_name":"Resilient Retrieval Models for Large Collection","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384643695","doi":"https://doi.org/10.1145/3539618.3591793"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3591793","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3591793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","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":"https://openalex.org/A5025051151","display_name":"Dipannita Podder","orcid":"https://orcid.org/0009-0001-4980-6158"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Dipannita Podder","raw_affiliation_strings":["Indian Institute of Technology, Kharagpur, Kharagpur, India"],"raw_orcid":"https://orcid.org/0009-0001-4980-6158","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5025051151"],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14100807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3492","last_page":"3492"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9991999864578247,"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":0.9991999864578247,"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/T10028","display_name":"Topic Modeling","score":0.9962000250816345,"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":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.8257128000259399},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.691743016242981},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6711688041687012},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.660951554775238},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5165225863456726},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.4601081311702728},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4550209939479828},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.430351197719574},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.41092735528945923},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3834649920463562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.353129506111145},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07145965099334717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8257128000259399},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.691743016242981},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6711688041687012},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.660951554775238},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5165225863456726},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.4601081311702728},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4550209939479828},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.430351197719574},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.41092735528945923},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3834649920463562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.353129506111145},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07145965099334717},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","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:10.1145/3539618.3591793","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3591793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","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":4,"referenced_works":["https://openalex.org/W1539587635","https://openalex.org/W1973289172","https://openalex.org/W3137305332","https://openalex.org/W4200605863"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395","https://openalex.org/W2387658907","https://openalex.org/W25098770"],"abstract_inverted_index":{"Modern":[0],"search":[1],"engines":[2],"employ":[3],"multi-stage":[4],"ranking":[5],"pipeline":[6],"to":[7],"balance":[8],"retrieval":[9,32,45],"efficiency":[10],"and":[11],"effectiveness":[12],"for":[13],"large":[14,27],"collections.":[15],"These":[16,47],"pipelines":[17,48],"retrieve":[18],"an":[19],"initial":[20],"set":[21],"of":[22],"candidate":[23,41],"documents":[24,42],"from":[25],"the":[26,52,62,67],"repository":[28],"by":[29,43],"some":[30],"cost-effective":[31],"model":[33],"(such":[34],"as":[35],"BM25,":[36],"LM),":[37],"then":[38],"re-rank":[39],"these":[40],"neural":[44],"models.":[46],"perform":[49],"well":[50],"if":[51],"first-stage":[53,63],"ranker":[54,64],"achieves":[55],"high":[56],"recall":[57],"[2].":[58],"To":[59],"achieve":[60],"this,":[61],"should":[65],"address":[66],"problems":[68],"in":[69],"milliseconds.":[70]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}