{"type":"ScholarlyArticle","title":"Optimal Greedy Diversity for Recommendation","authors":[{"name":"Azin Ashkan","slug":"azin-ashkan","given":"Azin","family":"Ashkan","affiliation":""},{"name":"Branislav Kveton","slug":"branislav-kveton","given":"Branislav","family":"Kveton","affiliation":""},{"name":"Shlomo Berkovsky","slug":"shlomo-berkovsky","given":"Shlomo","family":"Berkovsky","affiliation":""},{"name":"Zheng Wen","slug":"zheng-wen","given":"Zheng","family":"Wen","affiliation":""}],"abstract":"The need for diversification manifests in various recommendation use cases. In this work, we propose a novel approach to diversifying a list of recommended items, which maximizes the utility of the items subject to the increase in their diversity. From a technical perspective, the problem can be viewed as maximization of a modular function on the polytope of a submodular function, which can be solved optimally by a greedy method. We evaluate our approach in an offline analysis, which incorporates a number of baselines and metrics, and in two online user studies. In all the experiments, our method outperforms the baseline methods.","doi":null,"url":"https://ijcai.org/proceedings/2015/248","pdf":"https://ijcai.org/proceedings/2015/0248.pdf","markdown":"https://ijcai.org/proceedings/2015/248.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/248","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Recommender Systems","track":"Main Track","number":248,"pages":{"first":1742,"last":1747},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}