{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T21:45:34Z","timestamp":1784324734611,"version":"3.55.0"},"reference-count":37,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2016,3,8]],"date-time":"2016-03-08T00:00:00Z","timestamp":1457395200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2016,3,8]]},"abstract":"<jats:p>\n            Identifying semantic relations is a crucial step in discourse analysis and is useful for many applications in both language and speech technology. Automatic detection of\n            <jats:italic>Causal<\/jats:italic>\n            relations therefore has gained popularity in the literature within different frameworks. The aim of this article is the automatic detection and extraction of\n            <jats:italic>Causal<\/jats:italic>\n            relations that are explicitly expressed in Arabic texts. To fulfill this goal, a\n            <jats:italic>Pattern Recognizer<\/jats:italic>\n            model was developed to signal the presence of cause--effect information within sentences from nonspecific domain texts. This model incorporates approximately 700 linguistic patterns so that parts of the sentence representing the\n            <jats:italic>cause<\/jats:italic>\n            and those representing the\n            <jats:italic>effect<\/jats:italic>\n            can be distinguished. The patterns were constructed based on different sets of syntactic features by analyzing a large untagged Arabic corpus. In addition, the model was boosted with three independent algorithms to deal with certain types of grammatical particles that indicate causation. With this approach, the proposed model achieved an overall\n            <jats:italic>recall<\/jats:italic>\n            of 81% and a\n            <jats:italic>precision<\/jats:italic>\n            of 78%. Evaluation results revealed that the justification particles play a key role in detecting\n            <jats:italic>Causal<\/jats:italic>\n            relations. To the best of our knowledge, no previous studies have been dedicated to dealing with this type of relation in the Arabic language.\n          <\/jats:p>","DOI":"10.1145\/2800786","type":"journal-article","created":{"date-parts":[[2016,3,14]],"date-time":"2016-03-14T13:24:02Z","timestamp":1457961842000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Extracting Arabic Causal Relations Using Linguistic Patterns"],"prefix":"10.1145","volume":"15","author":[{"given":"Jawad","family":"Sadek","sequence":"first","affiliation":[{"name":"University of Salford, The Crescent, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farid","family":"Meziane","sequence":"additional","affiliation":[{"name":"University of Salford, The Crescent, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2016,3,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-013-9237-0"},{"key":"e_1_2_1_2_1","first-page":"207","article-title":"Arabic newspapers discourse: Rhetorical features, discourse markers, strategies and organization","volume":"27","author":"Al-Jarrah Mohammad","year":"2011","journal-title":"Damascus University Journal"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9582.1984.tb00734.x"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/1621474.1621559"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/1621474.1621559"},{"key":"e_1_2_1_6_1","volume-title":"Proceedings of the International Conference on Language Resources and Evaluation (LREC\u201908)","author":"Blancol Eduardo","year":"2008"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the 10th European Workshop on Knowledge Acquisition, Modeling and Management, 345--352","author":"Carcia Daniela","year":"1997"},{"key":"e_1_2_1_8_1","first-page":"65","article-title":"Empirical methods in information extraction","volume":"18","author":"Cardie Claire","year":"1997","journal-title":"Al Magazine"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/234173.234209"},{"key":"e_1_2_1_10_1","volume-title":"Proceedings of EMNLP\u201911","author":"Do Quang","year":"2011"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.3115\/1119312.1119322"},{"key":"e_1_2_1_12_1","volume-title":"Proceedings of the American Association for Artificial Intelligence (AAAI)-Spring Symposium, 15--25","author":"Girju Roxana","year":"2002"},{"key":"e_1_2_1_13_1","first-page":"31","article-title":"A decompositional analysis of causative verbs","volume":"12","author":"Gonsalves Renison","year":"1986","journal-title":"CUNYforum"},{"key":"e_1_2_1_14_1","volume-title":"Proceedings of the 23rd International Conference on Computational Linguistics, 395--402","author":"Green Spence","year":"2010"},{"key":"e_1_2_1_15_1","unstructured":"Nadia Haskour. 1990. 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