{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:34:20Z","timestamp":1723016060538},"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":[[2020,7]]},"abstract":"<jats:p>The Dirichlet Belief Network~(DirBN) has been recently proposed as a promising approach in learning interpretable deep latent representations for objects. \n\nIn this work, we leverage its interpretable modelling architecture and propose a deep dynamic probabilistic framework -- the Recurrent Dirichlet Belief Network~(Recurrent-DBN) -- to study interpretable hidden structures from dynamic relational data. The proposed Recurrent-DBN has the following merits: (1) it infers interpretable and organised hierarchical latent structures for objects within and across time steps; (2) it enables recurrent long-term temporal dependence modelling, which outperforms the one-order Markov descriptions in most of the dynamic probabilistic frameworks; (3) the computational cost scales to the number of positive links only. In addition, we develop a new inference strategy, which first upward-and-backward propagates latent counts and then downward-and-forward samples variables, to enable efficient Gibbs sampling for the Recurrent-DBN. We apply the Recurrent-DBN to dynamic relational data problems. The extensive experiment results on real-world data validate the advantages of the Recurrent-DBN over the state-of-the-art models in interpretable latent structure discovery and improved link prediction performance.<\/jats:p>","DOI":"10.24963\/ijcai.2020\/342","type":"proceedings-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T08:12:10Z","timestamp":1594195930000},"page":"2470-2476","source":"Crossref","is-referenced-by-count":2,"title":["Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling"],"prefix":"10.24963","author":[{"given":"Yaqiong","family":"Li","sequence":"first","affiliation":[{"name":"Centre for Artificial Intelligence, University of Technology Sydney"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuhui","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Mathematics & Statistics, University of New South Wales, Sydney"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Chen","sequence":"additional","affiliation":[{"name":"Centre for Artificial Intelligence, University of Technology Sydney"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Alberta"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Scott A.","family":"Sisson","sequence":"additional","affiliation":[{"name":"School of Mathematics & Statistics, University of New South Wales, Sydney"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-PRICAI-2020","name":"Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}","start":{"date-parts":[[2020,7,11]]},"theme":"Artificial Intelligence","location":"Yokohama, Japan","end":{"date-parts":[[2020,7,17]]}},"container-title":["Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T22:14:35Z","timestamp":1594246475000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2020\/342"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2020\/342","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}