{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,8,5]],"date-time":"2023-08-05T04:25:57Z","timestamp":1691209557847},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684062","type":"print"},{"value":"9781643684079","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,21]]},"abstract":"Integrations of case-based reasoning (CBR) with neural approaches are appealing because of their complimentary characteristics. This chapter presents research on neuro-symbolic integrations to support CBR, to reduce knowledge engineering and improve performance for CBR systems. It summarizes three strands of research: First, on extracting features for case retrieval from deep neural networks to use in concert with expert-generated features, second, on applying neural networks to learn to adapt the solutions of retrieved cases to fit new situations, and third, on harmonizing similarity learning with case adaptation learning, in order to focus retrieval on adaptable cases. It summarizes strengths, weaknesses and tradeoffs of these approaches, and points to future challenges for neuro-CBR integrations.<\/jats:p>","DOI":"10.3233\/faia230150","type":"book-chapter","created":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T06:44:49Z","timestamp":1691131489000},"source":"Crossref","is-referenced-by-count":0,"title":["Chapter 18. Enhancing Case-Based Reasoning with Neural Networks"],"prefix":"10.3233","author":[{"given":"David","family":"Leake","sequence":"first","affiliation":[{"name":"Indiana University"}]},{"given":"Zachary","family":"Wilkerson","sequence":"additional","affiliation":[{"name":"Indiana University"}]},{"given":"Xiaomeng","family":"Ye","sequence":"additional","affiliation":[{"name":"Berry College"}]},{"given":"David J.","family":"Crandall","sequence":"additional","affiliation":[{"name":"Indiana University"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Compendium of Neurosymbolic Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230150","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T06:44:52Z","timestamp":1691131492000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230150"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,21]]},"ISBN":["9781643684062","9781643684079"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230150","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,21]]}}}