{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T04:12:47Z","timestamp":1730002367693,"version":"3.28.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:p>In this paper, we present ASPEN, an answer set programming (ASP) implementation of a recently proposed declarative framework for collective entity resolution (ER). While an ASP encoding had been previously suggested, several practical issues had been neglected, most notably, the question of how to efficiently compute the (externally defined) similarity facts that are used in rule bodies. This leads us to propose new variants of the encodings (including Datalog approximations) and show how to employ different functionalities of ASP solvers to compute (maximal) solutions, and (approximations of) the sets of possible and certain merges. A comprehensive experimental evaluation of ASPEN on real-world datasets shows that the approach is promising, achieving high accuracy in real-life ER scenarios. Our experiments also yield useful insights into the relative merits of different types of (approximate) ER solutions, the impact of recursion, and factors influencing performance.<\/jats:p>","DOI":"10.24963\/kr.2024\/74","type":"proceedings-article","created":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T06:30:28Z","timestamp":1729924228000},"page":"788-799","source":"Crossref","is-referenced-by-count":0,"title":["ASPEN: ASP-Based System for Collective Entity Resolution"],"prefix":"10.24963","author":[{"given":"Zhiliang","family":"Xiang","sequence":"first","affiliation":[{"name":"Cardiff University, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meghyn","family":"Bienvenu","sequence":"additional","affiliation":[{"name":"Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, France"},{"name":"Japanese-French Laboratory for Informatics, CNRS, NII, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gianluca","family":"Cima","sequence":"additional","affiliation":[{"name":"Sapienza University of Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V\u00edctor","family":"Guti\u00e9rrez Basulto","sequence":"additional","affiliation":[{"name":"Cardiff University, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yazm\u00edn","family":"Ib\u00e1\u00f1ez Garc\u00eda","sequence":"additional","affiliation":[{"name":"Cardiff University, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}","theme":"Artificial Intelligence","location":"Hanoi, Vietnam","acronym":"KR-2024","number":"21","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Academic College of Tel-Aviv","European Association for Artificial Intelligence","National Science Foundation"],"start":{"date-parts":[[2024,11,1]]},"end":{"date-parts":[[2024,11,8]]}},"container-title":["Proceedings of the TwentyFirst International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T06:30:44Z","timestamp":1729924244000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2024\/74"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2024,11]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2024\/74","relation":{},"subject":[],"published":{"date-parts":[[2024,11]]}}}