{"id":"https://openalex.org/W3196905245","doi":"https://doi.org/10.1145/3471158.3472249","title":"Passage Similarity and Diversification in Non-factoid Question Answering","display_name":"Passage Similarity and Diversification in Non-factoid Question Answering","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3196905245","doi":"https://doi.org/10.1145/3471158.3472249","mag":"3196905245"},"language":"en","primary_location":{"id":"doi:10.1145/3471158.3472249","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3471158.3472249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 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/A5041500552","display_name":"Lakshmi Vikraman","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lakshmi Vikraman","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006981335","display_name":"Ali Montazeralghaem","orcid":"https://orcid.org/0000-0002-5467-1331"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Montazeralghaem","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027352823","display_name":"Helia Hashemi","orcid":"https://orcid.org/0000-0001-7258-7849"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Helia Hashemi","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105659698","display_name":"W. Bruce Croft","orcid":"https://orcid.org/0000-0003-2391-9629"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. Bruce Croft","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034070218","display_name":"James Allan","orcid":"https://orcid.org/0000-0003-0132-5694"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Allan","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5041500552"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63158123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"271","last_page":"280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9984999895095825,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9969000220298767,"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":0.8196525573730469},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.743238091468811},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6448017358779907},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5988621711730957},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.5977202653884888},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5574980974197388},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5405920743942261},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5395082831382751},{"id":"https://openalex.org/keywords/diversification","display_name":"Diversification (marketing strategy)","score":0.48935574293136597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4834945499897003},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.43961459398269653},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3513597548007965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8196525573730469},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.743238091468811},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6448017358779907},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5988621711730957},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.5977202653884888},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5574980974197388},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5405920743942261},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5395082831382751},{"id":"https://openalex.org/C180916674","wikidata":"https://www.wikidata.org/wiki/Q3711935","display_name":"Diversification (marketing strategy)","level":2,"score":0.48935574293136597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4834945499897003},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.43961459398269653},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3513597548007965},{"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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3471158.3472249","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3471158.3472249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"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":35,"referenced_works":["https://openalex.org/W1687668752","https://openalex.org/W1990473707","https://openalex.org/W2023188792","https://openalex.org/W2027445772","https://openalex.org/W2041565863","https://openalex.org/W2042980227","https://openalex.org/W2047804176","https://openalex.org/W2047952076","https://openalex.org/W2083305840","https://openalex.org/W2100902248","https://openalex.org/W2130395434","https://openalex.org/W2136542423","https://openalex.org/W2137819016","https://openalex.org/W2148367931","https://openalex.org/W2155188720","https://openalex.org/W2157391629","https://openalex.org/W2250539671","https://openalex.org/W2251202616","https://openalex.org/W2294145134","https://openalex.org/W2339630617","https://openalex.org/W2414781555","https://openalex.org/W2508661403","https://openalex.org/W2515565210","https://openalex.org/W2610935556","https://openalex.org/W2792379413","https://openalex.org/W2799019108","https://openalex.org/W2809897079","https://openalex.org/W2889563522","https://openalex.org/W2889757348","https://openalex.org/W2898700502","https://openalex.org/W2963846996","https://openalex.org/W2975606059","https://openalex.org/W3006471670","https://openalex.org/W3083591248","https://openalex.org/W3138773240"],"related_works":["https://openalex.org/W2974225181","https://openalex.org/W4288108740","https://openalex.org/W4287890973","https://openalex.org/W2153717697","https://openalex.org/W3018936175","https://openalex.org/W4312594379","https://openalex.org/W2180017908","https://openalex.org/W2887442125","https://openalex.org/W2289318896","https://openalex.org/W3107290838"],"abstract_inverted_index":{"The":[0,117],"rise":[1],"in":[2,14,85,93],"popularity":[3],"of":[4,28,42,78,120,140,172],"mobile":[5],"and":[6,34,58,110],"voice":[7],"search":[8],"has":[9],"led":[10],"to":[11,19,38,52,102,137,154,166],"a":[12,40,76,149,168],"shift":[13],"focus":[15],"from":[16],"document":[17],"retrieval":[18,23],"short":[20],"answer":[21,44,67],"passage":[22,145],"for":[24,124,130,143],"non-factoid":[25],"questions.":[26],"Some":[27],"the":[29,35,128,138],"questions":[30],"have":[31,90],"multiple":[32],"answers,":[33],"aim":[36],"is":[37,101,153],"retrieve":[39],"set":[41],"relevant":[43],"passages,":[45],"which":[46,112],"covers":[47],"all":[48],"these":[49,80],"alternatives.":[50],"Compared":[51],"documents,":[53],"answers":[54,174],"are":[55],"more":[56,61,132,150],"specific":[57],"typically":[59],"form":[60],"defined":[62],"types":[63],"or":[64],"groups.":[65],"Grouping":[66],"passages":[68],"based":[69,158],"on":[70],"strong":[71],"similarity":[72,147],"measures":[73],"may":[74],"provide":[75],"means":[77],"identifying":[79],"types.":[81],"Typically,":[82],"kNN":[83],"clustering":[84],"combination":[86],"with":[87],"term-based":[88],"representations":[89,106],"been":[91],"used":[92,165],"Information":[94],"Retrieval":[95],"(IR)":[96],"scenarios.":[97],"An":[98],"alternate":[99],"method":[100],"use":[103,155],"pre-trained":[104],"distributional":[105],"such":[107],"as":[108],"GloVe":[109],"BERT,":[111],"capture":[113],"additional":[114],"semantic":[115],"relationships.":[116],"recent":[118],"success":[119],"trained":[121],"neural":[122],"models":[123],"various":[125],"tasks":[126],"provides":[127],"motivation":[129],"generating":[131],"task-specific":[133],"representations.":[134],"However,":[135],"due":[136],"absence":[139],"large":[141],"datasets":[142],"incorporating":[144],"level":[146],"information,":[148],"feasible":[151],"alternative":[152],"weak":[156],"supervision":[157],"training.":[159],"This":[160],"information":[161],"can":[162],"then":[163],"be":[164],"generate":[167],"final":[169],"ranked":[170],"list":[171],"diversified":[173],"using":[175],"standard":[176],"diversification":[177],"algorithms.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
