{"id":"https://openalex.org/W3080661549","doi":"https://doi.org/10.1109/bigdata50022.2020.9378077","title":"TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity","display_name":"TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3080661549","doi":"https://doi.org/10.1109/bigdata50022.2020.9378077","mag":"3080661549"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.10856","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086385635","display_name":"Maryam Habibi","orcid":"https://orcid.org/0000-0002-3237-5080"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maryam Habibi","raw_affiliation_strings":["Humboldt Universit\u00e4t zu Berlin","Humboldt\u2010University of Berlin\u2028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humboldt Universit\u00e4t zu Berlin","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"Humboldt\u2010University of Berlin\u2028","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037135208","display_name":"Johannes Starlinger","orcid":"https://orcid.org/0000-0003-0832-9604"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Johannes Starlinger","raw_affiliation_strings":["Humboldt Universit\u00e4t zu Berlin","Humboldt\u2010University of Berlin\u2028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humboldt Universit\u00e4t zu Berlin","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"Humboldt\u2010University of Berlin\u2028","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055236937","display_name":"Ulf Leser","orcid":"https://orcid.org/0000-0003-2166-9582"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ulf Leser","raw_affiliation_strings":["Humboldt Universit\u00e4t zu Berlin","Humboldt\u2010University of Berlin\u2028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humboldt Universit\u00e4t zu Berlin","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"Humboldt\u2010University of Berlin\u2028","institution_ids":["https://openalex.org/I39343248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39343248"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08990566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"930","last_page":"937"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9990000128746033,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7444813251495361},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5735937356948853},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5636378526687622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5365858674049377},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5148886442184448},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.49644190073013306},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.4803427457809448},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.4429510831832886},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4296020567417145},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39613455533981323},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3784258961677551},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09914228320121765},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09397703409194946}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7444813251495361},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5735937356948853},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5636378526687622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5365858674049377},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5148886442184448},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.49644190073013306},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.4803427457809448},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4429510831832886},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4296020567417145},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39613455533981323},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3784258961677551},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09914228320121765},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09397703409194946}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2008.10856","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.10856","pdf_url":"https://arxiv.org/pdf/2008.10856","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3080661549","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2008.10856.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2008.10856","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2008.10856","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":"pmh:oai:arXiv.org:2008.10856","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.10856","pdf_url":"https://arxiv.org/pdf/2008.10856","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3080661549.pdf","grobid_xml":"https://content.openalex.org/works/W3080661549.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W102708294","https://openalex.org/W109189503","https://openalex.org/W161140159","https://openalex.org/W1576228976","https://openalex.org/W1595439448","https://openalex.org/W1721994796","https://openalex.org/W1902237438","https://openalex.org/W1930624869","https://openalex.org/W1967830139","https://openalex.org/W1969621019","https://openalex.org/W1975879668","https://openalex.org/W1996505782","https://openalex.org/W2020022499","https://openalex.org/W2064675550","https://openalex.org/W2066806792","https://openalex.org/W2104042955","https://openalex.org/W2108223890","https://openalex.org/W2115733720","https://openalex.org/W2127589108","https://openalex.org/W2131774270","https://openalex.org/W2137435551","https://openalex.org/W2137983211","https://openalex.org/W2138556038","https://openalex.org/W2138621090","https://openalex.org/W2140116426","https://openalex.org/W2147800946","https://openalex.org/W2153579005","https://openalex.org/W2156387975","https://openalex.org/W2162020046","https://openalex.org/W2171590421","https://openalex.org/W2290320465","https://openalex.org/W2305386159","https://openalex.org/W2341748398","https://openalex.org/W2527896214","https://openalex.org/W2604225376","https://openalex.org/W2736085271","https://openalex.org/W2753798143","https://openalex.org/W2768029001","https://openalex.org/W2788550262","https://openalex.org/W2899286282","https://openalex.org/W2913178646","https://openalex.org/W2953273646","https://openalex.org/W2963403868","https://openalex.org/W3086759766","https://openalex.org/W3091905774","https://openalex.org/W3146803896","https://openalex.org/W6604418364","https://openalex.org/W6606656084","https://openalex.org/W6635635861","https://openalex.org/W6682691769","https://openalex.org/W6728098186","https://openalex.org/W6735728188","https://openalex.org/W6739901393","https://openalex.org/W6740997287","https://openalex.org/W6744580074","https://openalex.org/W6755022349","https://openalex.org/W6755477022","https://openalex.org/W6782754321","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2961270449","https://openalex.org/W3193313290","https://openalex.org/W2974557215","https://openalex.org/W2897075155","https://openalex.org/W2997261377","https://openalex.org/W3135104291","https://openalex.org/W3107239392","https://openalex.org/W2112167375","https://openalex.org/W2251316775","https://openalex.org/W2251291469","https://openalex.org/W2799855306","https://openalex.org/W2107397692","https://openalex.org/W1748393397","https://openalex.org/W2966292222","https://openalex.org/W2164413279","https://openalex.org/W3154476387","https://openalex.org/W3025337893","https://openalex.org/W3194219952","https://openalex.org/W2964279163","https://openalex.org/W2996772168"],"abstract_inverted_index":{"Tables":[0,23],"are":[1,12,231],"a":[2,27,37,98,113,116,135,143,159,188,211,222],"popular":[3],"and":[4,45,126,153,172,180,216,227],"efficient":[5],"means":[6],"of":[7,18,32,39,79,92,119,121,164,178],"presenting":[8],"structured":[9],"information.":[10],"They":[11],"used":[13],"extensively":[14],"in":[15,132,210,221],"various":[16],"kinds":[17],"documents":[19],"including":[20],"web":[21],"pages.":[22],"display":[24],"information":[25],"as":[26,54,60,115],"two-dimensional":[28],"matrix,":[29],"the":[30,89,147],"semantics":[31],"which":[33],"is":[34,139],"conveyed":[35],"by":[36,205,217],"mixture":[38],"structure":[40],"(rows,":[41],"columns),":[42],"headers,":[43],"caption,":[44,123],"content.":[46],"Recent":[47],"research":[48],"has":[49],"started":[50],"to":[51,63,101,141],"consider":[52],"tables":[53,131],"first":[55],"class":[56],"objects,":[57],"not":[58],"just":[59],"an":[61,85],"addendum":[62],"texts,":[64],"yielding":[65],"interesting":[66],"results":[67],"for":[68,88,187],"problems":[69,81],"like":[70],"table":[71,73,103,114,166,200],"matching,":[72],"completion,":[74],"or":[75],"value":[76],"imputation.":[77],"All":[78],"these":[80],"inherently":[82],"rely":[83],"on":[84,203],"accurate":[86],"measure":[87],"semantic":[90,149],"similarity":[91,104,201,213],"two":[93,130,182],"tables.":[94],"We":[95],"present":[96],"TabSim,":[97],"novel":[99],"method":[100],"compute":[102,142],"scores":[105],"using":[106],"deep":[107],"neural":[108,137],"networks.":[109],"Conceptually,":[110],"TabSim":[111,197],"represents":[112],"learned":[117],"concatenation":[118],"embeddings":[120],"its":[122,124,127],"content,":[125],"structure.":[128],"Given":[129],"this":[133],"representation,":[134],"Siamese":[136],"network":[138],"trained":[140],"score":[144],"correlating":[145],"with":[146],"tables'":[148],"similarity.":[150],"To":[151],"train":[152],"evaluate":[154],"our":[155],"method,":[156],"we":[157],"created":[158],"gold":[160],"standard":[161],"corpus":[162],"consisting":[163],"1500":[165],"pairs":[167],"extracted":[168],"from":[169],"biomedical":[170],"articles":[171],"manually":[173],"scored":[174],"regarding":[175],"their":[176],"degree":[177],"similarity,":[179],"adopted":[181],"other":[183,199],"corpora":[184],"originally":[185],"developed":[186],"different":[189],"yet":[190],"similar":[191],"task.":[192],"Our":[193],"evaluation":[194],"shows":[195],"that":[196],"outperforms":[198],"measures":[202],"average":[204],"app.":[206,218],"7%":[207],"pp":[208,220],"F1-score":[209],"binary":[212],"classification":[214],"setting":[215],"1.5%":[219],"ranking":[223],"scenario.":[224],"The":[225],"codes":[226],"resources":[228],"introduced":[229],"here":[230],"available":[232],"at":[233],"https://github.com/Marhabibi/TabSim.":[234]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}