{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T21:49:02Z","timestamp":1770068942995,"version":"3.49.0"},"reference-count":0,"publisher":"Slovenian Association Informatika","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCAI"],"abstract":"<jats:p>This study proposes an Adaptive Multidimensional Fusion Network (AMFN) for financial market trend forecasting. The model integrates heterogeneous data sources through a multidimensional data fusion module, combining historical price and volume data with external information such as macroeconomic indicators and sentiment indices. An adaptive temporal processing module is employed to model time-varying dependencies and regime shifts in market behavior, while a dynamic decision-tree prediction module captures nonlinear patterns in the fused representations. Experiments are conducted on multiple financial datasets, including the S&amp;P 500 Index, China A-share market, and Gold Futures, using a rolling time-window evaluation to avoid information leakage. The AMFN model achieves lower MSE and MAE and higher R\u00b2 than traditional SVM and LSTM baselines, with up to 24.4% relative improvement in forecasting accuracy. These results demonstrate that AMFN provides interpretable, stable, and robust trend predictions across diverse market environments.<\/jats:p>","DOI":"10.31449\/inf.v50i5.10720","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T10:25:35Z","timestamp":1770027935000},"source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Multidimensional Fusion Network with Dynamic Decision Trees for Financial Market Trend Forecasting"],"prefix":"10.31449","volume":"50","author":[{"given":"Sheng","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"16141","published-online":{"date-parts":[[2026,2,2]]},"container-title":["Informatica"],"original-title":[],"link":[{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/10720\/6422","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/10720\/6422","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T10:25:35Z","timestamp":1770027935000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/view\/10720"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,2]]},"references-count":0,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,2,2]]}},"URL":"https:\/\/doi.org\/10.31449\/inf.v50i5.10720","relation":{},"ISSN":["1854-3871","0350-5596"],"issn-type":[{"value":"1854-3871","type":"electronic"},{"value":"0350-5596","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2,2]]}}}