{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T12:10:21Z","timestamp":1764850221137,"version":"3.46.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686387","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,2]]},"abstract":"<jats:p>Disambiguating references to legal provisions in court decisions is challenging when abbreviations map to multiple candidate laws, yet it is crucial because reliable reference resolution supports legal information retrieval. We present a self-supervised, graph-based method that constructs a weighted co-occurrence graph from court decisions, where nodes are legal provisions and edge weights reflect their co-occurrence frequency. Ambiguous references are resolved by measuring distances from context provisions using a multi-source Dijkstra algorithm, selecting the closest candidate. Experiments show that the approach improves accuracy over naive baselines, provides confidence scores for reliability, and delivers a practical disambiguation method, while our study also contributes an annotated dataset for future research.<\/jats:p>","DOI":"10.3233\/faia251601","type":"book-chapter","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T12:05:14Z","timestamp":1764849914000},"source":"Crossref","is-referenced-by-count":0,"title":["A Self-Supervised Method for Legal Reference Resolution"],"prefix":"10.3233","author":[{"given":"\u0160imon","family":"Horv\u00e1t","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice"}]},{"given":"D\u00e1vid","family":"Varga","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice"}]},{"given":"Peter","family":"Gursk\u00fd","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice"}]},{"given":"Nicol","family":"Fedurcov\u00e1","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice"}]},{"given":"Samuel","family":"Baran","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice"}]},{"given":"Zolt\u00e1n","family":"Szopl\u00e1k","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Legal Knowledge and Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251601","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T12:05:24Z","timestamp":1764849924000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251601"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,2]]},"ISBN":["9781643686387"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251601","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,2]]}}}