{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T16:20:52Z","timestamp":1764433252643,"version":"3.41.0"},"reference-count":40,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2019,6,10]],"date-time":"2019-06-10T00:00:00Z","timestamp":1560124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"ADAPT Centre"},{"name":"NSFC project","award":["61379086, 61602284, 61602285, and 61602282"],"award-info":[{"award-number":["61379086, 61602284, 61602285, and 61602282"]}]},{"DOI":"10.13039\/501100001602","name":"Science Foundation Ireland","doi-asserted-by":"crossref","award":["13\/RC\/2106"],"award-info":[{"award-number":["13\/RC\/2106"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Shandong Provincial Natural Science Foundation, China","award":["ZR2015FQ009"],"award-info":[{"award-number":["ZR2015FQ009"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2019,12,31]]},"abstract":"<jats:p>Most of the syntax-based metrics obtain the similarity by comparing the sub-structures extracted from the trees of hypothesis and reference. These sub-structures cannot represent all the information in the trees because their lengths are limited. To sufficiently use the reference syntax information, a new automatic evaluation metric is proposed based on the dependency parsing model. First, a dependency parsing model is trained using the reference dependency tree for each sentence. Then, the hypothesis is parsed by this dependency parsing model and the corresponding hypothesis dependency tree is generated. The quality of hypothesis can be judged by the quality of the hypothesis dependency tree. Unigram F-score is included in the new metric so that lexicon similarity is obtained. According to experimental results, the proposed metric can perform better than METEOR and BLEU on system level and get comparable results with METEOR on sentence level. To further improve the performance, we also propose a combined metric which gets the best performance on the sentence level and on the system level.<\/jats:p>","DOI":"10.1145\/3312573","type":"journal-article","created":{"date-parts":[[2019,6,11]],"date-time":"2019-06-11T13:28:16Z","timestamp":1560259696000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Machine Translation Evaluation Metric Based on Dependency Parsing Model"],"prefix":"10.1145","volume":"18","author":[{"given":"Hui","family":"Yu","sequence":"first","affiliation":[{"name":"Business School, Shandong Normal University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weizhi","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shandong Normal University, Jinan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shouxun","family":"Lin","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qun","family":"Liu","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Hong Kong SAR, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,6,10]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and\/or Summarization. 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