{"id":"https://openalex.org/W3083330919","doi":"https://doi.org/10.1145/3409256.3409828","title":"Utilizing Axiomatic Perturbations to Guide Neural Ranking Models","display_name":"Utilizing Axiomatic Perturbations to Guide Neural Ranking Models","publication_year":2020,"publication_date":"2020-09-05","ids":{"openalex":"https://openalex.org/W3083330919","doi":"https://doi.org/10.1145/3409256.3409828","mag":"3083330919"},"language":"en","primary_location":{"id":"doi:10.1145/3409256.3409828","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3409256.3409828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM SIGIR on International Conference on Theory of 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/A5016350146","display_name":"Zitong Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zitong Cheng","raw_affiliation_strings":["University of Delaware, Newark, DE, USA"],"affiliations":[{"raw_affiliation_string":"University of Delaware, Newark, DE, USA","institution_ids":["https://openalex.org/I86501945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101716412","display_name":"Hui Fang","orcid":"https://orcid.org/0009-0003-1904-787X"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Fang","raw_affiliation_strings":["University of Delaware, Newark, DE, USA"],"affiliations":[{"raw_affiliation_string":"University of Delaware, Newark, DE, USA","institution_ids":["https://openalex.org/I86501945"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016350146"],"corresponding_institution_ids":["https://openalex.org/I86501945"],"apc_list":null,"apc_paid":null,"fwci":0.2669,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64841447,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"153","last_page":"156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9970999956130981,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.989799976348877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7863349914550781},{"id":"https://openalex.org/keywords/axiom","display_name":"Axiom","score":0.7783462405204773},{"id":"https://openalex.org/keywords/axiomatic-system","display_name":"Axiomatic system","score":0.7301305532455444},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6737929582595825},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.568932294845581},{"id":"https://openalex.org/keywords/axiomatic-design","display_name":"Axiomatic design","score":0.5551234483718872},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5489839911460876},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5464325547218323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5151392221450806},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3746568560600281},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10565739870071411},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06188735365867615}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7863349914550781},{"id":"https://openalex.org/C167729594","wikidata":"https://www.wikidata.org/wiki/Q17736","display_name":"Axiom","level":2,"score":0.7783462405204773},{"id":"https://openalex.org/C125773388","wikidata":"https://www.wikidata.org/wiki/Q792542","display_name":"Axiomatic system","level":3,"score":0.7301305532455444},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6737929582595825},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.568932294845581},{"id":"https://openalex.org/C84170951","wikidata":"https://www.wikidata.org/wiki/Q647225","display_name":"Axiomatic design","level":3,"score":0.5551234483718872},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5489839911460876},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5464325547218323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5151392221450806},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3746568560600281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10565739870071411},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06188735365867615},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C137335462","wikidata":"https://www.wikidata.org/wiki/Q380772","display_name":"Lean manufacturing","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3409256.3409828","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3409256.3409828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM SIGIR on International Conference on Theory of 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":14,"referenced_works":["https://openalex.org/W136907812","https://openalex.org/W1549770780","https://openalex.org/W1999822363","https://openalex.org/W2082359527","https://openalex.org/W2097432019","https://openalex.org/W2134557008","https://openalex.org/W2152784831","https://openalex.org/W2162432120","https://openalex.org/W2162697159","https://openalex.org/W2170738476","https://openalex.org/W2286300105","https://openalex.org/W2536015822","https://openalex.org/W2927996276","https://openalex.org/W2963165092"],"related_works":["https://openalex.org/W2528271379","https://openalex.org/W2607982435","https://openalex.org/W2366624134","https://openalex.org/W1623032916","https://openalex.org/W1508537345","https://openalex.org/W1981489863","https://openalex.org/W1946769093","https://openalex.org/W2282950774","https://openalex.org/W2218361189","https://openalex.org/W2534359342"],"abstract_inverted_index":{"Axiomatic":[0],"approaches":[1,24,74],"aim":[2],"to":[3,8,67,70,75],"utilize":[4,71],"reasonable":[5],"retrieval":[6,14,36,87,92],"constraints":[7,88],"guide":[9,76],"the":[10,20,27,31,52,72,77,82],"search":[11],"for":[12],"optimal":[13],"models.":[15],"Existing":[16],"studies":[17],"have":[18,47],"shown":[19],"effectiveness":[21],"of":[22,33,40],"axiomatic":[23,73],"in":[25,51],"improving":[26],"performance":[28],"through":[29],"either":[30],"derivation":[32],"new":[34],"basic":[35],"models":[37,46,57,84],"or":[38],"modifications":[39],"existing":[41],"ones.":[42],"Recently,":[43],"neural":[44],"network":[45],"attracted":[48],"more":[49],"attention":[50],"research":[53],"community.":[54],"Since":[55],"these":[56],"are":[58],"learned":[59,83],"from":[60],"training":[61,78],"data,":[62],"it":[63],"would":[64],"be":[65],"interesting":[66],"study":[68],"how":[69],"process":[79],"so":[80],"that":[81],"can":[85],"satisfy":[86],"and":[89],"achieve":[90],"better":[91],"performance.":[93]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}