{"id":"https://openalex.org/W3012644370","doi":"https://doi.org/10.1145/3366423.3379995","title":"Ad Hoc Table Retrieval using Intrinsic and Extrinsic Similarities","display_name":"Ad Hoc Table Retrieval using Intrinsic and Extrinsic Similarities","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3012644370","doi":"https://doi.org/10.1145/3366423.3379995","mag":"3012644370"},"language":"en","primary_location":{"id":"doi:10.1145/3366423.3379995","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3379995","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3366423.3379995","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002899918","display_name":"Roee Shraga","orcid":"https://orcid.org/0000-0001-8803-8481"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Roee Shraga","raw_affiliation_strings":["Technion - Israel Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Technion - Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071848619","display_name":"Haggai Roitman","orcid":"https://orcid.org/0000-0002-5260-2287"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haggai Roitman","raw_affiliation_strings":["IBM"],"affiliations":[{"raw_affiliation_string":"IBM","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021095324","display_name":"Guy Feigenblat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guy Feigenblat","raw_affiliation_strings":["IBM"],"affiliations":[{"raw_affiliation_string":"IBM","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043925652","display_name":"Mustafa Canim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mustafa Canim","raw_affiliation_strings":["IBM"],"affiliations":[{"raw_affiliation_string":"IBM","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002899918"],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":2.9645,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91243181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"322","issue":null,"first_page":"2479","last_page":"2485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9962000250816345,"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":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.8245383501052856},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.7664732336997986},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.7144767045974731},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6734645366668701},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5661693811416626},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5091373324394226},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4740811586380005},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4725579619407654},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.466872900724411},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.41096267104148865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40680307149887085},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36278092861175537},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24755090475082397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8245383501052856},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.7664732336997986},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.7144767045974731},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6734645366668701},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5661693811416626},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5091373324394226},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4740811586380005},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4725579619407654},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.466872900724411},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.41096267104148865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40680307149887085},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36278092861175537},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24755090475082397},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3366423.3379995","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3379995","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3366423.3379995","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3379995","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1577504169","https://openalex.org/W1967830139","https://openalex.org/W1982410540","https://openalex.org/W1990589796","https://openalex.org/W2000431947","https://openalex.org/W2008840123","https://openalex.org/W2019509999","https://openalex.org/W2066806792","https://openalex.org/W2067833899","https://openalex.org/W2077428231","https://openalex.org/W2092364718","https://openalex.org/W2108223890","https://openalex.org/W2132083030","https://openalex.org/W2162020046","https://openalex.org/W2293116569","https://openalex.org/W2342096063","https://openalex.org/W2398606196","https://openalex.org/W2736085271","https://openalex.org/W2788152782","https://openalex.org/W2788550262","https://openalex.org/W2811146799","https://openalex.org/W2890872166","https://openalex.org/W2899286282","https://openalex.org/W2963759819","https://openalex.org/W2964133178","https://openalex.org/W2969723769","https://openalex.org/W3099839495","https://openalex.org/W3102264439","https://openalex.org/W4206765718","https://openalex.org/W4393074830"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W3160516639","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395","https://openalex.org/W2387658907"],"abstract_inverted_index":{"Given":[0],"a":[1,13,23,52,90,104],"keyword":[2],"query,":[3],"the":[4,17,67,72],"ad":[5],"hoc":[6],"table":[7,25,61,107],"retrieval":[8,108],"task":[9],"aims":[10],"at":[11],"retrieving":[12],"ranked":[14],"list":[15],"of":[16,55,74,114],"top-k":[18],"most":[19],"relevant":[20],"tables":[21],"in":[22,103],"given":[24],"corpus.":[26],"Previous":[27],"works":[28],"have":[29],"primarily":[30],"focused":[31],"on":[32],"designing":[33],"table-centric":[34],"lexical":[35],"and":[36,58],"semantic":[37],"features,":[38],"which":[39,110],"could":[40],"be":[41],"utilized":[42],"for":[43,63,78],"learning-to-rank":[44],"(LTR)":[45],"tables.":[46],"In":[47],"this":[48,79,82],"work,":[49],"we":[50,70,84],"make":[51],"novel":[53],"use":[54],"intrinsic":[56],"(passage-based)":[57],"extrinsic":[59],"(manifold-based)":[60],"similarities":[62,77],"enhanced":[64],"retrieval.":[65],"Using":[66],"WikiTables":[68],"benchmark,":[69],"study":[71],"merits":[73],"utilizing":[75],"such":[76],"task.":[80],"To":[81],"end,":[83],"combine":[85],"both":[86],"similarity":[87],"types":[88],"via":[89],"simple,":[91],"yet":[92],"an":[93],"effective,":[94],"cascade":[95],"re-ranking":[96],"approach.":[97],"Overall,":[98],"our":[99],"proposed":[100],"approach":[101],"results":[102],"significantly":[105],"better":[106],"quality,":[109],"even":[111],"transcends":[112],"that":[113],"strong":[115],"semantically-rich":[116],"baselines.":[117]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-28T06:11:35.319607","created_date":"2025-10-10T00:00:00"}