{"id":"https://openalex.org/W2975822827","doi":"https://doi.org/10.1145/3341981.3344219","title":"A Study of Query Performance Prediction for Answer Quality Determination","display_name":"A Study of Query Performance Prediction for Answer Quality Determination","publication_year":2019,"publication_date":"2019-09-26","ids":{"openalex":"https://openalex.org/W2975822827","doi":"https://doi.org/10.1145/3341981.3344219","mag":"2975822827"},"language":"en","primary_location":{"id":"doi:10.1145/3341981.3344219","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341981.3344219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGIR 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/A5071848619","display_name":"Haggai Roitman","orcid":"https://orcid.org/0000-0002-5260-2287"},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Haggai Roitman","raw_affiliation_strings":["IBM Research - Haifa, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007046423","display_name":"Shai Erera","orcid":null},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Shai Erera","raw_affiliation_strings":["IBM Research - Haifa, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021095324","display_name":"Guy Feigenblat","orcid":null},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Guy Feigenblat","raw_affiliation_strings":["IBM Research - Haifa, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071848619"],"corresponding_institution_ids":["https://openalex.org/I4210167297"],"apc_list":null,"apc_paid":null,"fwci":0.5601,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.75304127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"43","last_page":"46"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9991000294685364,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9987000226974487,"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/computer-science","display_name":"Computer science","score":0.8641070127487183},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.7188690900802612},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6902102828025818},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6562039852142334},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.6157640814781189},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5740478038787842},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.5422552227973938},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5236434936523438},{"id":"https://openalex.org/keywords/result-set","display_name":"Result set","score":0.5154803395271301},{"id":"https://openalex.org/keywords/web-query-classification","display_name":"Web query classification","score":0.48274582624435425},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.47135820984840393},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.44050899147987366},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3758230209350586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2755209803581238}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8641070127487183},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.7188690900802612},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6902102828025818},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6562039852142334},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.6157640814781189},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5740478038787842},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.5422552227973938},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5236434936523438},{"id":"https://openalex.org/C4969071","wikidata":"https://www.wikidata.org/wiki/Q7316353","display_name":"Result set","level":3,"score":0.5154803395271301},{"id":"https://openalex.org/C118689300","wikidata":"https://www.wikidata.org/wiki/Q7978614","display_name":"Web query classification","level":4,"score":0.48274582624435425},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.47135820984840393},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.44050899147987366},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3758230209350586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2755209803581238},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3341981.3344219","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341981.3344219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1957644519","https://openalex.org/W2149427297","https://openalex.org/W2155712036","https://openalex.org/W2964154091"],"related_works":["https://openalex.org/W2096432151","https://openalex.org/W1601704076","https://openalex.org/W1999370257","https://openalex.org/W2114566577","https://openalex.org/W2967117036","https://openalex.org/W3198925789","https://openalex.org/W2744669951","https://openalex.org/W2103552971","https://openalex.org/W1601713026","https://openalex.org/W1584051879"],"abstract_inverted_index":{"We":[0],"study":[1],"a":[2,9,16,19,24,61,73],"constrained":[3],"retrieval":[4,87],"setting":[5],"in":[6],"which":[7,59],"either":[8],"single":[10],"qualitative":[11],"answer":[12,29,55],"is":[13],"provided":[14],"as":[15],"response":[17],"to":[18,40,45],"user-query":[20,25],"or":[21,43],"none.":[22],"Given":[23],"and":[26,88],"the":[27,34,96],"\"best\"":[28],"that":[30],"was":[31],"retrieved":[32],"from":[33,72],"underlying":[35],"search":[36,82],"engine,":[37],"we":[38,52,94],"wish":[39],"determine":[41],"whether":[42],"not":[44],"accept":[46],"it.":[47],"To":[48],"address":[49],"this":[50],"challenge,":[51],"propose":[53],"an":[54],"quality":[56],"determination":[57],"approach":[58],"leverages":[60],"novel":[62],"set":[63],"of":[64,75,98],"answer-level":[65],"query":[66],"performance":[67],"prediction":[68],"(QPP)":[69],"features,":[70],"derived":[71],"couple":[74],"recent":[76],"discriminative":[77],"QPP":[78],"frameworks.":[79],"Using":[80],"various":[81],"benchmarks":[83],"with":[84],"both":[85],"ad-hoc":[86],"non-factoid":[89],"question":[90],"answering":[91],"(QA)":[92],"tasks,":[93],"demonstrate":[95],"effectiveness":[97],"our":[99],"approach.":[100]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}