{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T11:40:43Z","timestamp":1774352443355,"version":"3.50.1"},"reference-count":33,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T00:00:00Z","timestamp":1773360000000},"content-version":"vor","delay-in-days":71,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:p>\n                    AI\u2010Cinema is a hybrid neural\u2010symbolic framework addressing the critical challenge of preserving cultural authenticity in Arabic movie scenario generation. The framework integrates transformer\u2010based neural language models (AraT5\u2010base and AraGPT2\u2010medium) with symbolic reasoning encoded in OWL\u2010DL ontologies and SWRL rules to ensure linguistic fluency, narrative coherence, and cultural preservation. AI\u2010Cinema introduces a three\u2010tier architecture comprising a data layer, cultural embedding layer, and scenario generation layer. Central to its design is an attention\u2010based cultural embedding mechanism leveraging\n                    <jats:italic>ArabicVerbNet<\/jats:italic>\n                    (12,500 culturally annotated verbs) and\n                    <jats:italic>ArabicNameNet<\/jats:italic>\n                    (3653 names with regional annotations), complemented by a mathematically grounded harmony function that dynamically balances neural generation with symbolic constraints. In experiments on 2740 Arabic narratives, AI\u2010Cinema achieves a BLEU\u20104 score of 32.76 (\u00b1 0.6), representing a 5.0% relative improvement over AraBERT\u2010Gen (\n                    <jats:italic>p<\/jats:italic>\n                    &lt; 0.01, paired bootstrap test) and a 27.5 percentage point gain in cultural preservation metric (CPM) compared with MARBERT\u2010Gen (82.3% vs. 54.8%). The framework maintains 92.3% dialectal accuracy across Modern Standard Arabic and six regional dialects, with explicit evaluation of code\u2010switching scenarios. Expert evaluations by 30 Arabic literature scholars demonstrate strong interannotator agreement (Fleiss\u2019\n                    <jats:italic>\u03ba<\/jats:italic>\n                    = 0.78,\n                    <jats:italic>p<\/jats:italic>\n                    &lt; 0.001), with 87% of evaluators rating generated narratives as culturally authentic (score \u2265 4 on a 5\u2010point scale). Current limitations include reduced performance on underrepresented dialects (Yemeni: 85.6% and Sudanese: 86.1%) and complex code\u2010switching scenarios (76.3% for 3+ dialects). The framework incorporates transparent labeling mechanisms for AI\u2010generated cultural content to address authenticity concerns. All resources are publicly available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/Mossab82\/AI-Cinema\">https:\/\/github.com\/Mossab82\/AI-Cinema<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1155\/cplx\/9978799","type":"journal-article","created":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T06:11:04Z","timestamp":1773468664000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI\u2010Cinema: A Hybrid Framework for Arabic Movie Scenario Generation With Traditional Storytelling and Cultural Dialogs"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4216-1721","authenticated-orcid":false,"given":"Mossab","family":"Ibrahim","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4906-9837","authenticated-orcid":false,"given":"Pablo","family":"Gerv\u00e1s","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7659-1482","authenticated-orcid":false,"given":"Gonzalo","family":"M\u00e9ndez","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2026,3,13]]},"reference":[{"key":"e_1_2_13_1_2","doi-asserted-by":"publisher","DOI":"10.1145\/3731443.3771364"},{"key":"e_1_2_13_2_2","unstructured":"Abdul-MageedM. 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