{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T10:39:09Z","timestamp":1721039949260},"reference-count":25,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition Letters"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1016\/j.patrec.2022.05.016","type":"journal-article","created":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T22:32:49Z","timestamp":1652740369000},"page":"174-180","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"C","title":["Task-specific dependency-based word embedding methods"],"prefix":"10.1016","volume":"159","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-4742-1158","authenticated-orcid":false,"given":"Chengwei","family":"Wei","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-9760-8343","authenticated-orcid":false,"given":"Bin","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-9474-5035","authenticated-orcid":false,"given":"C.-C. Jay","family":"Kuo","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.patrec.2022.05.016_bib0001","series-title":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","first-page":"740","article-title":"A fast and accurate dependency parser using neural networks","author":"Chen","year":"2014"},{"key":"10.1016\/j.patrec.2022.05.016_bib0002","series-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"785","article-title":"XGBoost: a scalable tree boosting system","author":"Chen","year":"2016"},{"key":"10.1016\/j.patrec.2022.05.016_bib0003","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.patrec.2016.06.012","article-title":"Representation learning for very short texts using weighted word embedding aggregation","volume":"80","author":"De Boom","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.patrec.2022.05.016_bib0004","series-title":"LREC","first-page":"4585","article-title":"Universal stanford dependencies: a cross-linguistic typology","volume":"vol.\u00a014","author":"De Marneffe","year":"2014"},{"key":"10.1016\/j.patrec.2022.05.016_sbref0005","series-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)","first-page":"4171","article-title":"BERT: pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2019"},{"key":"10.1016\/j.patrec.2022.05.016_bib0006","series-title":"Studies in Linguistic Analysis","article-title":"A synopsis of linguistic theory, 1930\u20131955","author":"Firth","year":"1957"},{"issue":"2\u20133","key":"10.1016\/j.patrec.2022.05.016_bib0007","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1080\/00437956.1954.11659520","article-title":"Distributional structure","volume":"10","author":"Harris","year":"1954","journal-title":"Word"},{"key":"10.1016\/j.patrec.2022.05.016_bib0008","series-title":"Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","first-page":"1490","article-title":"Dependency based embeddings for sentence classification tasks","author":"Komninos","year":"2016"},{"key":"10.1016\/j.patrec.2022.05.016_bib0009","series-title":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","first-page":"302","article-title":"Dependency-based word embeddings","author":"Levy","year":"2014"},{"key":"10.1016\/j.patrec.2022.05.016_bib0010","first-page":"2177","article-title":"Neural word embedding as implicit matrix factorization","volume":"27","author":"Levy","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patrec.2022.05.016_bib0011","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1162\/tacl_a_00134","article-title":"Improving distributional similarity with lessons learned from word embeddings","volume":"3","author":"Levy","year":"2015","journal-title":"Trans. Assoc. Comput.Linguist."},{"key":"10.1016\/j.patrec.2022.05.016_bib0012","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Training and evaluating improved dependency-based word embeddings","author":"Li","year":"2018"},{"key":"10.1016\/j.patrec.2022.05.016_bib0013","series-title":"Proceedings of the 27th International Conference on Computational Linguistics","first-page":"2023","article-title":"Task-oriented word embedding for text classification","author":"Liu","year":"2018"},{"key":"10.1016\/j.patrec.2022.05.016_bib0014","series-title":"Twenty-Ninth AAAI Conference on Artificial Intelligence","article-title":"Topical word embeddings","author":"Liu","year":"2015"},{"key":"10.1016\/j.patrec.2022.05.016_bib0015","unstructured":"T. Mikolov, K. Chen, G. Corrado, J. Dean, Efficient estimation of word representations in vector space, arXiv preprint arXiv:1301.3781 (2013)."},{"issue":"2","key":"10.1016\/j.patrec.2022.05.016_bib0016","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1162\/coli.2007.33.2.161","article-title":"Dependency-based construction of semantic space models","volume":"33","author":"Pad\u00f3","year":"2007","journal-title":"Comput. Linguist."},{"key":"10.1016\/j.patrec.2022.05.016_bib0017","series-title":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","first-page":"1532","article-title":"GloVe: global vectors for word representation","author":"Pennington","year":"2014"},{"key":"10.1016\/j.patrec.2022.05.016_sbref0018","series-title":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)","first-page":"2227","article-title":"Deep contextualized word representations","author":"Peters","year":"2018"},{"key":"10.1016\/j.patrec.2022.05.016_sbref0019","series-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations","article-title":"Stanza: a python natural language processing toolkit for many human languages","author":"Qi","year":"2020"},{"key":"10.1016\/j.patrec.2022.05.016_bib0020","series-title":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","first-page":"1555","article-title":"Learning sentiment-specific word embedding for twitter sentiment classification","author":"Tang","year":"2014"},{"key":"10.1016\/j.patrec.2022.05.016_bib0021","doi-asserted-by":"crossref","first-page":"2146","DOI":"10.1109\/TASLP.2020.3008390","article-title":"SBERT-WK: a sentence embedding method by dissecting bert-based word models","volume":"28","author":"Wang","year":"2020","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"10.1016\/j.patrec.2022.05.016_bib0022","series-title":"2020 25th International Conference on Pattern Recognition (ICPR)","first-page":"119","article-title":"Efficient sentence embedding via semantic subspace analysis","author":"Wang","year":"2021"},{"key":"10.1016\/j.patrec.2022.05.016_bib0023","doi-asserted-by":"crossref","unstructured":"B. Wang, C.-C. J. Kuo, H. Li, Just rank: rethinking evaluation with word and sentence similarities, Proceedings of the 60th An-nual Meeting of the Association for Computational Linguistics (Volume1: Long Papers), Association for Computational Linguistics, Dublin, Ireland, 2022, pp. 6060\u20136077. URL: https:\/\/aclanthology.org\/2022.acl-long.419.","DOI":"10.18653\/v1\/2022.acl-long.419"},{"key":"10.1016\/j.patrec.2022.05.016_bib0024","first-page":"649","article-title":"Character-level convolutional networks for text classification","volume":"28","author":"Zhang","year":"2015","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patrec.2022.05.016_bib0025","series-title":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","first-page":"1393","article-title":"Bilingual word embeddings for phrase-based machine translation","author":"Zou","year":"2013"}],"container-title":["Pattern Recognition Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S016786552200174X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S016786552200174X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T18:01:16Z","timestamp":1673287276000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S016786552200174X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":25,"alternative-id":["S016786552200174X"],"URL":"https:\/\/doi.org\/10.1016\/j.patrec.2022.05.016","relation":{},"ISSN":["0167-8655"],"issn-type":[{"value":"0167-8655","type":"print"}],"subject":[],"published":{"date-parts":[[2022,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Task-specific dependency-based word embedding methods","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition Letters","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patrec.2022.05.016","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}