{"id":"https://openalex.org/W2890872166","doi":"https://doi.org/10.1145/3234944.3234946","title":"An Extended Query Performance Prediction Framework Utilizing Passage-Level Information","display_name":"An Extended Query Performance Prediction Framework Utilizing Passage-Level Information","publication_year":2018,"publication_date":"2018-09-10","ids":{"openalex":"https://openalex.org/W2890872166","doi":"https://doi.org/10.1145/3234944.3234946","mag":"2890872166"},"language":"en","primary_location":{"id":"doi:10.1145/3234944.3234946","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3234944.3234946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 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, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research, Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5071848619"],"corresponding_institution_ids":["https://openalex.org/I4210167297"],"apc_list":null,"apc_paid":null,"fwci":3.1415,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.93427619,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9994000196456909,"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":0.9994000196456909,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9973999857902527,"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":0.9968000054359436,"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":0.8743839263916016},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.6423969864845276},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.5731635689735413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5220553874969482},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4646527171134949},{"id":"https://openalex.org/keywords/online-aggregation","display_name":"Online aggregation","score":0.4510747790336609},{"id":"https://openalex.org/keywords/sargable","display_name":"Sargable","score":0.4349218010902405},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.34773439168930054},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.33028554916381836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8743839263916016},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.6423969864845276},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.5731635689735413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5220553874969482},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4646527171134949},{"id":"https://openalex.org/C24028149","wikidata":"https://www.wikidata.org/wiki/Q7094056","display_name":"Online aggregation","level":5,"score":0.4510747790336609},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.4349218010902405},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.34773439168930054},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.33028554916381836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3234944.3234946","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3234944.3234946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1577504169","https://openalex.org/W1985471546","https://openalex.org/W1990791207","https://openalex.org/W2004545875","https://openalex.org/W2014415866","https://openalex.org/W2019509999","https://openalex.org/W2028521145","https://openalex.org/W2032750961","https://openalex.org/W2034441832","https://openalex.org/W2046950757","https://openalex.org/W2067833899","https://openalex.org/W2068902033","https://openalex.org/W2077428231","https://openalex.org/W2078537247","https://openalex.org/W2079168273","https://openalex.org/W2087131461","https://openalex.org/W2087408015","https://openalex.org/W2087818911","https://openalex.org/W2093390569","https://openalex.org/W2093514947","https://openalex.org/W2130900715","https://openalex.org/W2136542423","https://openalex.org/W2169213601","https://openalex.org/W2234701313","https://openalex.org/W2336203772","https://openalex.org/W2740635163","https://openalex.org/W2742009068","https://openalex.org/W2758859575","https://openalex.org/W2759472822","https://openalex.org/W2798470324","https://openalex.org/W4240913316","https://openalex.org/W4246858749"],"related_works":["https://openalex.org/W3125756434","https://openalex.org/W2096359267","https://openalex.org/W185198413","https://openalex.org/W2150741898","https://openalex.org/W2184296057","https://openalex.org/W2901901036","https://openalex.org/W2362460270","https://openalex.org/W4321649654","https://openalex.org/W2538384344","https://openalex.org/W1793997780"],"abstract_inverted_index":{"We":[0],"show":[1],"that":[2,56],"document-level":[3,75],"post-retrieval":[4,45],"query":[5,15,28,38,89],"performance":[6],"prediction":[7,16,29,34,83],"(QPP)":[8],"methods":[9,19,55],"are":[10,60],"mostly":[11],"suited":[12,63],"for":[13,64],"short":[14],"tasks;":[17],"such":[18],"perform":[20],"significantly":[21],"worse":[22],"in":[23],"verbose":[24,65],"(long":[25],"and":[26,76],"informative)":[27],"settings.":[30,67],"To":[31],"address":[32],"the":[33],"quality":[35],"gap":[36],"among":[37],"lengths,":[39],"we":[40],"propose":[41],"a":[42,80],"novel":[43],"passage-level":[44,58,77],"QPP":[46,54,66],"framework.":[47],"Our":[48],"empirical":[49],"analysis":[50],"demonstrates":[51],"that,":[52],"those":[53],"utilize":[57,73],"information":[59,78],"much":[61],"better":[62],"Moreover,":[68],"our":[69],"proposed":[70],"predictors,":[71],"which":[72,84],"both":[74],"provide":[79],"more":[81],"robust":[82],"is":[85],"less":[86],"sensitive":[87],"to":[88],"length.":[90]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}