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The objective is to translate a meta-path to its comparable explainable meta-paths that perform similarly in terms of recommendation but have higher explainability compared to the given one. We propose a definition of meta-path explainability to determine comparable explainable meta-paths and a meta-path grammar that allows comparable explainable meta-paths to be formed in a similar way as sentences in human languages. Based on this grammar, we propose a meta-path translation model, a sequence-to-sequence (Seq2Seq) model to translate a long and complicated meta-path to its comparable explainable meta-paths. Two novel datasets for meta-path translation were generated based on two real-world recommendation datasets. The experiments were conducted on these generated datasets. The results show that our model outperformed state-of-the-art Seq2Seq baselines regarding meta-path translation and maintained a better trade-off between accuracy and diversity\/readability in predicting comparable explainable meta-paths. These results indicate that our model can effectively generate a group of explainable meta-paths as alternative explanations for those recommendations based on any given long\/complicated meta-path.<\/jats:p>","DOI":"10.1145\/3625828","type":"journal-article","created":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T16:07:10Z","timestamp":1695917230000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Explainable Meta-Path Based Recommender Systems"],"prefix":"10.1145","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2685-0738","authenticated-orcid":false,"given":"Thanet","family":"Markchom","sequence":"first","affiliation":[{"name":"University of Reading, United Kingdom, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4408-4528","authenticated-orcid":false,"given":"Huizhi","family":"Liang","sequence":"additional","affiliation":[{"name":"Newcastle University, United Kingdom, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2194-4871","authenticated-orcid":false,"given":"James","family":"Ferryman","sequence":"additional","affiliation":[{"name":"University of Reading, United Kingdom, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,11,27]]},"reference":[{"issue":"9","key":"e_1_3_3_2_2","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1111\/j.1467-9280.2006.01787.x","article-title":"Contextual diversity, not word frequency, determines word-naming and lexical decision times","volume":"17","author":"Adelman James S.","year":"2006","unstructured":"James S. 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