{"id":"https://openalex.org/W3033478637","doi":"https://doi.org/10.4018/ijec.2020070105","title":"A New Hybrid Document Clustering for PRF-Based Automatic Query Expansion Approach for Effective IR","display_name":"A New Hybrid Document Clustering for PRF-Based Automatic Query Expansion Approach for Effective IR","publication_year":2020,"publication_date":"2020-06-02","ids":{"openalex":"https://openalex.org/W3033478637","doi":"https://doi.org/10.4018/ijec.2020070105","mag":"3033478637"},"language":"en","primary_location":{"id":"doi:10.4018/ijec.2020070105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijec.2020070105","pdf_url":null,"source":{"id":"https://openalex.org/S129960573","display_name":"International Journal of e-Collaboration","issn_l":"1548-3673","issn":["1548-3673","1548-3681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of e-Collaboration","raw_type":"journal-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/A5038010120","display_name":"Yogesh Gupta","orcid":"https://orcid.org/0000-0002-4561-7210"},"institutions":[{"id":"https://openalex.org/I1323093577","display_name":"BML Munjal University","ror":"https://ror.org/058ay3j75","country_code":"IN","type":"education","lineage":["https://openalex.org/I1323093577"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Yogesh Gupta","raw_affiliation_strings":["BML Munjal University, Haryana, India"],"affiliations":[{"raw_affiliation_string":"BML Munjal University, Haryana, India","institution_ids":["https://openalex.org/I1323093577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101420668","display_name":"Ashish Saini","orcid":"https://orcid.org/0000-0003-3061-2342"},"institutions":[{"id":"https://openalex.org/I178254495","display_name":"Dayalbagh Educational Institute","ror":"https://ror.org/04q4j2f69","country_code":"IN","type":"education","lineage":["https://openalex.org/I178254495"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Saini","raw_affiliation_strings":["Dayalbagh Educational Institute, India"],"affiliations":[{"raw_affiliation_string":"Dayalbagh Educational Institute, India","institution_ids":["https://openalex.org/I178254495"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038010120"],"corresponding_institution_ids":["https://openalex.org/I1323093577"],"apc_list":null,"apc_paid":null,"fwci":0.2931,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55316932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"16","issue":"3","first_page":"73","last_page":"95"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9955000281333923,"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"}},{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.994700014591217,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9925000071525574,"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/query-expansion","display_name":"Query expansion","score":0.8027952313423157},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6992736458778381},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.6617645025253296},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5714985132217407},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5632280111312866},{"id":"https://openalex.org/keywords/sargable","display_name":"Sargable","score":0.5527556538581848},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5394173264503479},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5119982361793518},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.501030445098877},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.47998639941215515},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4522666037082672},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42685768008232117},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.4267445206642151},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.3974979817867279},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3292272388935089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2754248082637787},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.2699562907218933}],"concepts":[{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.8027952313423157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6992736458778381},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.6617645025253296},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5714985132217407},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5632280111312866},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.5527556538581848},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5394173264503479},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5119982361793518},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.501030445098877},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.47998639941215515},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4522666037082672},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42685768008232117},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.4267445206642151},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.3974979817867279},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3292272388935089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2754248082637787},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.2699562907218933},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4018/ijec.2020070105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijec.2020070105","pdf_url":null,"source":{"id":"https://openalex.org/S129960573","display_name":"International Journal of e-Collaboration","issn_l":"1548-3673","issn":["1548-3673","1548-3681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of e-Collaboration","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1482214997","https://openalex.org/W1525341925","https://openalex.org/W1971785050","https://openalex.org/W1989885825","https://openalex.org/W1992113527","https://openalex.org/W2084319893","https://openalex.org/W2109535575","https://openalex.org/W2150011485","https://openalex.org/W2156235561","https://openalex.org/W2158844415","https://openalex.org/W2186351772","https://openalex.org/W2277011981","https://openalex.org/W2547051197","https://openalex.org/W2608770662","https://openalex.org/W2741307002","https://openalex.org/W2752783125","https://openalex.org/W2892322198","https://openalex.org/W2917528797","https://openalex.org/W2963680465","https://openalex.org/W4246858749","https://openalex.org/W6628905179","https://openalex.org/W6631459773"],"related_works":["https://openalex.org/W2006459955","https://openalex.org/W2096359267","https://openalex.org/W3125756434","https://openalex.org/W2184296057","https://openalex.org/W4386051213","https://openalex.org/W203907944","https://openalex.org/W2146885082","https://openalex.org/W185198413","https://openalex.org/W2538384344","https://openalex.org/W3049728138"],"abstract_inverted_index":{"Automatic":[0],"query":[1,39,97,119],"expansion":[2],"(AQE)":[3],"is":[4,56,90,108,142],"an":[5],"effective":[6,81],"measure":[7],"to":[8,73,92,126],"improve":[9],"information":[10],"retrieval":[11],"performance":[12,134,165],"by":[13],"including":[14],"additional":[15,96],"terms":[16,98,120,131],"in":[17,44,58,139],"a":[18,35,46,78,100,112],"user":[19],"query.":[20],"The":[21,133,154],"pseudo":[22],"relevance":[23],"feedback":[24],"(PRF)":[25],"method":[26,116],"employed":[27],"for":[28,51],"AQE":[29,54],"so":[30],"far":[31],"has":[32],"suffered":[33],"from":[34],"major":[36],"problem":[37],"of":[38,103,135,157,166],"drift.":[40],"Therefore,":[41],"keeping":[42],"it":[43],"view,":[45],"new":[47,79],"hybrid":[48,82],"document":[49,75],"clustering":[50],"PRF":[52],"based":[53],"approach":[55,89],"proposed":[57,168],"the":[59,136,159,163,167],"present":[60],"article.":[61],"In":[62],"this,":[63],"Fuzzy":[64,85],"logic":[65],"and":[66,80,84,144],"Particle":[67],"Swarm":[68],"Optimization":[69],"(PSO)":[70],"are":[71,123],"used":[72,125],"construct":[74],"clusters.":[76],"Further,":[77],"PSO":[83],"logic-based":[86],"term":[87],"weighting":[88],"followed":[91],"find":[93],"more":[94],"suitable":[95],"using":[99],"weighted":[101],"score":[102],"four":[104],"IR":[105],"evidences":[106],"which":[107],"considered":[109],"maximized.":[110],"Moreover,":[111],"combined":[113],"semantic":[114],"filtering":[115],"along":[117],"with":[118,146],"re-weighting":[121],"algorithms":[122],"also":[124],"remove":[127],"noisy":[128],"or":[129],"irrelevant":[130],"semantically.":[132],"presented":[137],"approaches":[138,148,161],"this":[140],"article":[141],"tested":[143,160],"compared":[145],"other":[147],"on":[149],"three":[150],"benchmark":[151],"data":[152],"sets.":[153],"comparative":[155],"analysis":[156],"all":[158],"illustrates":[162],"superior":[164],"approach.":[169]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
