{"id":"https://openalex.org/W7164020249","doi":"https://doi.org/10.48550/arxiv.2606.08426","title":"CritLens: Visual Analytics for Criteria Discovery in Review-Based Decision Making","display_name":"CritLens: Visual Analytics for Criteria Discovery in Review-Based Decision Making","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164020249","doi":"https://doi.org/10.48550/arxiv.2606.08426"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.08426","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138228587","display_name":"Hongjia Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Hongjia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138256068","display_name":"Shuai Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138237804","display_name":"Hongxin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hongxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138240370","display_name":"Wei Chen (23863)","orcid":"https://orcid.org/0000-0002-5255-4166"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.6722000241279602,"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/T10799","display_name":"Data Visualization and Analytics","score":0.6722000241279602,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.053599998354911804,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0357000008225441,"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/visual-analytics","display_name":"Visual analytics","score":0.6277999877929688},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5938000082969666},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.548799991607666},{"id":"https://openalex.org/keywords/analytic-hierarchy-process","display_name":"Analytic hierarchy process","score":0.5338000059127808},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.49729999899864197},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.45179998874664307},{"id":"https://openalex.org/keywords/everyday-life","display_name":"Everyday life","score":0.4178999960422516},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.4106999933719635}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6947000026702881},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.6277999877929688},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5938000082969666},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.548799991607666},{"id":"https://openalex.org/C87345402","wikidata":"https://www.wikidata.org/wiki/Q485202","display_name":"Analytic hierarchy process","level":2,"score":0.5338000059127808},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.49729999899864197},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C2779018934","wikidata":"https://www.wikidata.org/wiki/Q1129653","display_name":"Everyday life","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40059998631477356},{"id":"https://openalex.org/C199004533","wikidata":"https://www.wikidata.org/wiki/Q210127","display_name":"Balanced scorecard","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C186116695","wikidata":"https://www.wikidata.org/wiki/Q5249226","display_name":"Decision analysis","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2784999907016754},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.26489999890327454},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.08426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8216873407363892,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"CritLens,":[2],"a":[3,128,153],"visual":[4],"analytics":[5],"system":[6],"that":[7],"helps":[8],"users":[9,40,106],"build":[10],"personalized":[11],"multi-criteria":[12],"decision":[13,91,133],"models":[14],"from":[15],"review":[16,143],"text.":[17,144],"In":[18],"everyday":[19],"decisions":[20],"--":[21,27],"choosing":[22],"equipment,":[23],"hotels,":[24],"or":[25,35,45],"restaurants":[26],"evaluation":[28],"criteria":[29,108],"are":[30,58],"either":[31],"preset":[32],"by":[33,37,81,110],"platforms":[34],"generated":[36],"LLMs,":[38],"leaving":[39],"unable":[41],"to":[42,84,140],"discover,":[43],"adjust,":[44],"verify":[46],"them":[47],"against":[48],"the":[49,103,111,141,158],"underlying":[50],"evidence.":[51],"This":[52],"is":[53],"problematic":[54],"because":[55],"many":[56],"preferences":[57],"latent:":[59],"they":[60,122,135],"surface":[61],"only":[62],"upon":[63],"encountering":[64],"specific":[65],"reviews,":[66],"and":[67,126,131,152],"any":[68],"fixed":[69],"framework":[70],"risks":[71],"overlooking":[72],"low-frequency":[73],"but":[74],"decisive":[75],"details.":[76],"CritLens":[77],"addresses":[78],"this":[79],"gap":[80,100],"using":[82],"LLMs":[83],"transform":[85],"reviews":[86],"into":[87],"an":[88,148],"initial":[89,112],"AHP":[90,119],"model,":[92],"then":[93],"supporting":[94],"iterative,":[95],"human-in-the-loop":[96],"refinement.":[97],"Through":[98],"coverage":[99],"detection":[101],"in":[102],"embedding":[104],"space,":[105],"discover":[107],"missed":[109],"model;":[113],"through":[114,127],"interactive":[115],"weight":[116],"adjustment":[117],"under":[118],"consistency":[120],"constraints,":[121],"express":[123],"personal":[124],"priorities;":[125],"multi-level":[129],"scorecard":[130],"exportable":[132],"report,":[134],"trace":[136],"every":[137],"ranking":[138],"back":[139],"original":[142],"Two":[145],"case":[146],"studies,":[147],"eight-participant":[149],"user":[150],"study,":[151],"quantitative":[154],"consistency-repair":[155],"experiment":[156],"demonstrate":[157],"system's":[159],"effectiveness.":[160]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-10T00:00:00"}