{"id":"https://openalex.org/W2897132999","doi":"https://doi.org/10.1145/3242587.3242617","title":"Facilitating Document Reading by Linking Text and Tables","display_name":"Facilitating Document Reading by Linking Text and Tables","publication_year":2018,"publication_date":"2018-10-11","ids":{"openalex":"https://openalex.org/W2897132999","doi":"https://doi.org/10.1145/3242587.3242617","mag":"2897132999"},"language":"en","primary_location":{"id":"doi:10.1145/3242587.3242617","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3242587.3242617","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3242587.3242617","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3242587.3242617","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100374581","display_name":"Dae Hyun Kim","orcid":"https://orcid.org/0000-0002-8657-9986"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dae Hyun Kim","raw_affiliation_strings":["Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067722075","display_name":"Enamul Hoque","orcid":"https://orcid.org/0000-0002-9789-6645"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Enamul Hoque","raw_affiliation_strings":["Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079709359","display_name":"Juho Kim","orcid":"https://orcid.org/0000-0001-6348-4127"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Juho Kim","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology, Daejeon, Rebublic of Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology, Daejeon, Rebublic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045835385","display_name":"Maneesh Agrawala","orcid":"https://orcid.org/0000-0002-8996-7327"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maneesh Agrawala","raw_affiliation_strings":["Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100374581"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":2.3692,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":{"value":0.91414055,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"423","last_page":"434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.996999979019165,"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":0.8430689573287964},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.7944916486740112},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.708271861076355},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7045950293540955},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6756030321121216},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5996382832527161},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.5580546259880066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49721816182136536},{"id":"https://openalex.org/keywords/table-of-contents","display_name":"Table of contents","score":0.43095964193344116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1864534318447113},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18333947658538818},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11091068387031555},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09827080368995667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8430689573287964},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.7944916486740112},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.708271861076355},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7045950293540955},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6756030321121216},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5996382832527161},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.5580546259880066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49721816182136536},{"id":"https://openalex.org/C68476402","wikidata":"https://www.wikidata.org/wiki/Q1456936","display_name":"Table of contents","level":2,"score":0.43095964193344116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1864534318447113},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18333947658538818},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11091068387031555},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09827080368995667},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3242587.3242617","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3242587.3242617","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3242587.3242617","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3242587.3242617","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3242587.3242617","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3242587.3242617","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1704278647","display_name":null,"funder_award_id":"III-1714647","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2897132999.pdf","grobid_xml":"https://content.openalex.org/works/W2897132999.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W102708294","https://openalex.org/W1614298861","https://openalex.org/W1894075015","https://openalex.org/W2048349970","https://openalex.org/W2053604034","https://openalex.org/W2066806792","https://openalex.org/W2068562326","https://openalex.org/W2082129984","https://openalex.org/W2083928261","https://openalex.org/W2094728533","https://openalex.org/W2096765155","https://openalex.org/W2098516643","https://openalex.org/W2101964891","https://openalex.org/W2108223890","https://openalex.org/W2123442489","https://openalex.org/W2139893662","https://openalex.org/W2251812060","https://openalex.org/W2515845560","https://openalex.org/W2522351341","https://openalex.org/W2552839021","https://openalex.org/W2595457065","https://openalex.org/W2620949368","https://openalex.org/W2725765016","https://openalex.org/W2831517801","https://openalex.org/W2915027006","https://openalex.org/W2962897020","https://openalex.org/W2963599677","https://openalex.org/W2964078224","https://openalex.org/W2964116568","https://openalex.org/W4241512756"],"related_works":["https://openalex.org/W2375873920","https://openalex.org/W2082438799","https://openalex.org/W2948670949","https://openalex.org/W4288047943","https://openalex.org/W1966986837","https://openalex.org/W2360138227","https://openalex.org/W3037187668","https://openalex.org/W2146114872","https://openalex.org/W2392060890","https://openalex.org/W4365808155"],"abstract_inverted_index":{"Document":[0],"authors":[1],"commonly":[2],"use":[3],"tables":[4,14,55,91],"to":[5],"support":[6],"arguments":[7],"presented":[8],"in":[9],"the":[10,19,32,61,114,126,141],"text.":[11],"But,":[12],"because":[13],"are":[15],"usually":[16],"separate":[17],"from":[18],"main":[20],"body":[21],"text,":[22],"readers":[23,165],"must":[24],"split":[25],"their":[26],"attention":[27],"between":[28,76],"different":[29],"parts":[30],"of":[31,90,103,113],"document.":[33],"We":[34,67],"present":[35],"an":[36,69],"interactive":[37,161],"document":[38,43,162,179],"reader":[39,59,163],"that":[40,86,156],"automatically":[41],"links":[42],"text":[44,78],"with":[45,92,168],"corresponding":[46,169],"table":[47,63,80,130,145,170],"cells.":[48,131],"Readers":[49],"can":[50],"select":[51],"a":[52,100,177],"sentence":[53,77],"(or":[54,65],"cells)":[56],"and":[57,79,96,147,174],"our":[58,108,160],"highlights":[60],"relevant":[62],"cells":[64,81,146,171],"sentences).":[66],"provide":[68],"automatic":[70],"pipeline":[71,109],"for":[72,82],"extracting":[73],"such":[74,158],"references":[75],"existing":[83],"PDF":[84],"documents":[85],"combines":[87],"structural":[88],"analysis":[89],"natural":[93],"language":[94],"processing":[95],"rule-based":[97],"matching.":[98],"On":[99],"test":[101],"corpus":[102],"330":[104],"(sentence,":[105],"table)":[106],"pairs,":[107],"correctly":[110],"extracts":[111],"48.8%":[112],"references.":[115],"An":[116],"additional":[117],"30.5%":[118],"contain":[119,135],"only":[120],"false":[121,136],"negatives":[122],"(FN)":[123],"errors":[124,139],"--":[125,140],"reference":[127,142],"is":[128],"missing":[129],"The":[132],"remaining":[133],"20.7%":[134],"positives":[137],"(FP)":[138],"includes":[143],"extraneous":[144],"could":[148],"therefore":[149],"mislead":[150],"readers.":[151],"A":[152],"user":[153],"study":[154],"finds":[155],"despite":[157],"errors,":[159],"helps":[164],"match":[166],"sentences":[167],"more":[172],"accurately":[173],"quickly":[175],"than":[176],"baseline":[178],"reader.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
