{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:14:40Z","timestamp":1740100480792,"version":"3.37.3"},"reference-count":47,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006505","name":"Swiss Re","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006505","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,15]]},"DOI":"10.1109\/bigdata52589.2021.9671828","type":"proceedings-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T20:39:16Z","timestamp":1642106356000},"page":"5043-5052","source":"Crossref","is-referenced-by-count":3,"title":["ConvTab: A Context-Preserving, Convolutional Model for Ad-Hoc Table Retrieval"],"prefix":"10.1109","author":[{"given":"Vibhav","family":"Agarwal","sequence":"first","affiliation":[]},{"given":"Akansha","family":"Bhardwaj","sequence":"additional","affiliation":[]},{"given":"Paolo","family":"Rosso","sequence":"additional","affiliation":[]},{"given":"Philippe","family":"Cudre-Mauroux","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"journal-title":"The Cross-Entropy Method A Unified Approach to Combinatorial Optimization Monte-Carlo Simulation and Machine Learning","year":"2013","author":"rubinstein","key":"ref38"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380257"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-47765-6"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"article-title":"Scientific table search using keyword queries","year":"2017","author":"gao","key":"ref30"},{"key":"ref37","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"2013","journal-title":"Advances in neural information processing systems"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-25007-6_25"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966182"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390177"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.14778\/2336664.2336665"},{"key":"ref40","volume":"463","author":"baeza-yates","year":"1999","journal-title":"Modern Information Retrieval"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2015.05.001"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213848"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186067"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331333"},{"article-title":"Tabvec: Table vectors for classification of web tables","year":"2018","author":"ghasemi-gol","key":"ref15"},{"key":"ref16","first-page":"510","article-title":"Entity matching on web tables: a table embeddings approach for blocking","author":"gentile","year":"2017","journal-title":"EDBT"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3379995"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401044"},{"article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","year":"2018","author":"devlin","key":"ref19"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1174"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.14778\/2002938.2002939"},{"key":"ref27","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.10484","article-title":"Understanding the semantic structures of tables with a hybrid deep neural network architecture","author":"nishida","year":"2017","journal-title":"Thirty-First AAAI Conference on Artificial Intelligence"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1921005"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623749"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005681"},{"article-title":"Harnessing the deep web: Present and future","year":"2009","author":"madhavan","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2501511.2501516"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465276"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/SDS49233.2020.00013"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687750"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.14778\/1453856.1453916"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1561\/1500000016"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.398"},{"article-title":"Multilayer perceptron, fuzzy sets, classifiaction","year":"1992","author":"pal","key":"ref45"},{"key":"ref22","first-page":"109","article-title":"Okapi at trec-3","volume":"109","author":"robertson","year":"1995"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273513"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401120"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963461"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159730"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401906"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-56608-5_66"},{"article-title":"An empirical study of learning to rank for entity search proceedings of the 39th annual international acm sigir conference on research and development in information retrieval,(sigir 2016)","year":"2016","author":"chen","key":"ref44"},{"key":"ref26","first-page":"1","article-title":"Learning cell embeddings for understanding table layouts","author":"ghasemi-gol","year":"2020","journal-title":"Knowledge and Information Systems"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-009-9123-y"},{"article-title":"Efficient estimation of word representations in vector space","year":"2013","author":"mikolov","key":"ref25"}],"event":{"name":"2021 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2021,12,15]]},"location":"Orlando, FL, USA","end":{"date-parts":[[2021,12,18]]}},"container-title":["2021 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9671263\/9671273\/09671828.pdf?arnumber=9671828","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T22:07:14Z","timestamp":1674425234000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9671828\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,15]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/bigdata52589.2021.9671828","relation":{},"subject":[],"published":{"date-parts":[[2021,12,15]]}}}