{"id":"https://openalex.org/W7131444452","doi":"https://doi.org/10.1109/ccwc67433.2026.11393808","title":"Rule-Based Classification and Clustering for Thematic Analysis of Research Papers","display_name":"Rule-Based Classification and Clustering for Thematic Analysis of Research Papers","publication_year":2026,"publication_date":"2026-01-05","ids":{"openalex":"https://openalex.org/W7131444452","doi":"https://doi.org/10.1109/ccwc67433.2026.11393808"},"language":null,"primary_location":{"id":"doi:10.1109/ccwc67433.2026.11393808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc67433.2026.11393808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5024386695","display_name":"Mehedi Hasan Abid","orcid":null},"institutions":[{"id":"https://openalex.org/I194028371","display_name":"University of Regina","ror":"https://ror.org/03dzc0485","country_code":"CA","type":"education","lineage":["https://openalex.org/I194028371"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mehedi Hasan Abid","raw_affiliation_strings":["University of Regina,Department of Computer Science,Regina,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Regina,Department of Computer Science,Regina,Canada","institution_ids":["https://openalex.org/I194028371"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065251213","display_name":"Jingtao Yao","orcid":"https://orcid.org/0000-0002-1337-4218"},"institutions":[{"id":"https://openalex.org/I194028371","display_name":"University of Regina","ror":"https://ror.org/03dzc0485","country_code":"CA","type":"education","lineage":["https://openalex.org/I194028371"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"JingTao Yao","raw_affiliation_strings":["University of Regina,Department of Computer Science,Regina,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Regina,Department of Computer Science,Regina,Canada","institution_ids":["https://openalex.org/I194028371"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I194028371"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1473295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"0305","last_page":"0310"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.34380000829696655,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.34380000829696655,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.05590000003576279,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.04659999907016754,"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/categorization","display_name":"Categorization","score":0.734499990940094},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7167999744415283},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6751000285148621},{"id":"https://openalex.org/keywords/thematic-map","display_name":"Thematic map","score":0.5327000021934509},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4860000014305115},{"id":"https://openalex.org/keywords/conceptual-clustering","display_name":"Conceptual clustering","score":0.42829999327659607},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.3668000102043152},{"id":"https://openalex.org/keywords/thematic-analysis","display_name":"Thematic analysis","score":0.3643999993801117}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7526000142097473},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.734499990940094},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7167999744415283},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6751000285148621},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5551000237464905},{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.5327000021934509},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4860000014305115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4684999883174896},{"id":"https://openalex.org/C39235581","wikidata":"https://www.wikidata.org/wiki/Q5158434","display_name":"Conceptual clustering","level":5,"score":0.42829999327659607},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.42100000381469727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3919000029563904},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.3668000102043152},{"id":"https://openalex.org/C74196892","wikidata":"https://www.wikidata.org/wiki/Q7781188","display_name":"Thematic analysis","level":3,"score":0.3643999993801117},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.35589998960494995},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.302700012922287},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.2948000133037567},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.2782000005245209},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C2781083858","wikidata":"https://www.wikidata.org/wiki/Q17327049","display_name":"Scientific literature","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C2778109090","wikidata":"https://www.wikidata.org/wiki/Q7781195","display_name":"Thematic structure","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc67433.2026.11393808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc67433.2026.11393808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC)","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":26,"referenced_works":["https://openalex.org/W1907286193","https://openalex.org/W2043566294","https://openalex.org/W2095601341","https://openalex.org/W2184378182","https://openalex.org/W2327531583","https://openalex.org/W2406978180","https://openalex.org/W2621485502","https://openalex.org/W2776393547","https://openalex.org/W2801314826","https://openalex.org/W2888840545","https://openalex.org/W2897159192","https://openalex.org/W2961191798","https://openalex.org/W2992258031","https://openalex.org/W3111278950","https://openalex.org/W3149778443","https://openalex.org/W3160856016","https://openalex.org/W3163723672","https://openalex.org/W3184058630","https://openalex.org/W4200398992","https://openalex.org/W4281646566","https://openalex.org/W4297860676","https://openalex.org/W4309811661","https://openalex.org/W4313371821","https://openalex.org/W4323351031","https://openalex.org/W4391788942","https://openalex.org/W4400811537"],"related_works":[],"abstract_inverted_index":{"The":[0,42,78,102,115],"rapid":[1],"expansion":[2],"of":[3,34,58],"scientific":[4],"publications":[5],"has":[6],"intensified":[7],"the":[8,28,65,70,98,120,128,136,157,162],"need":[9],"for":[10,27],"faster":[11],"and":[12,31,40,49,55,113,126,132,160],"more":[13],"consistent":[14],"approaches":[15],"to":[16,52,69,96,151],"organizing":[17],"research":[18,35,153],"evidence.":[19],"This":[20],"work":[21],"presents":[22],"a":[23,75,87],"domainindependent,":[24],"keyword-driven":[25],"framework":[26,43,137],"automatic":[29],"categorization":[30],"thematic":[32],"grouping":[33],"articles":[36],"using":[37,86,111],"only":[38],"titles":[39],"abstracts.":[41],"combines":[44],"rule-based":[45],"labeling,":[46],"expert":[47],"validation,":[48],"unsupervised":[50],"clustering":[51],"support":[53],"transparent":[54],"reproducible":[56],"analysis":[57],"publication":[59],"trends.":[60],"To":[61],"demonstrate":[62],"its":[63],"use,":[64],"approach":[66],"is":[67],"applied":[68],"Three-Way":[71],"Clustering":[72],"literature":[73],"as":[74],"case":[76,116],"study.":[77],"workflow":[79],"assigns":[80],"preliminary":[81],"technology-oriented":[82,131],"or":[83,144],"application-oriented":[84,133],"labels":[85,95],"simple":[88],"keyword":[89,158],"model.":[90],"Expert":[91],"review":[92],"refines":[93],"these":[94],"form":[97],"final":[99],"ground":[100],"truth.":[101],"validated":[103],"abstracts":[104],"are":[105],"then":[106],"grouped":[107],"into":[108],"coherent":[109],"themes":[110],"TF-IDF":[112],"Kmeans.":[114],"study":[117],"illustrates":[118],"how":[119],"process":[121],"can":[122,148],"summarize":[123],"methodological":[124],"directions":[125],"identify":[127],"balance":[129],"between":[130],"research.":[134],"Because":[135],"does":[138],"not":[139],"rely":[140],"on":[141],"training":[142],"data":[143],"domain-specific":[145],"models,":[146],"it":[147],"be":[149],"adapted":[150],"other":[152],"fields":[154],"by":[155],"redefining":[156],"sets":[159],"applying":[161],"same":[163],"automated":[164],"workflow.":[165]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-26T00:00:00"}
