Proceedings of the 7th ACM conference on Recommender systems最新文献_第8页

Hybrid event recommendation using linked data and user diversity 使用关联数据和用户多样性的混合事件推荐

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507171

Houda Khrouf, Raphael Troncy

{"title":"Hybrid event recommendation using linked data and user diversity","authors":"Houda Khrouf, Raphael Troncy","doi":"10.1145/2507157.2507171","DOIUrl":"https://doi.org/10.1145/2507157.2507171","url":null,"abstract":"An ever increasing number of social services offer thousands of diverse events per day. Users tend to be overwhelmed by the massive amount of information available, especially with limited browsing options perceived in many event web services. To alleviate this information overload, a recommender system becomes a vital component for assisting users selecting relevant events. However, such system faces a number of challenges owed to the the inherent complex nature of an event. In this paper, we propose a novel hybrid approach built on top of Semantic Web. On the one hand, we use a content-based system enriched with Linked Data to overcome the data sparsity, a problem induced by the transiency of events. On the other hand, we incorporate a collaborative filtering to involve the social aspect, an influential feature in decision making. This hybrid system is enhanced by the integration of a user diversity model designed to detect user propensity towards specific topics. We show how the hybridization of CB+CF systems and the integration of interest diversity features are important to improve predictions. Experimental results demonstrate the effectiveness of our approach using precision and recall measures.","PeriodicalId":225573,"journal":{"name":"Proceedings of the 7th ACM conference on Recommender systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127172598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 125

Set-oriented personalized ranking for diversified top-n recommendation 面向集合的个性化排名，多样化的top-n推荐

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507207

Ruilong Su, Li'ang Yin, Kailong Chen, Yong Yu

引用次数: 33

Distributed matrix factorization with mapreduce using a series of broadcast-joins 使用一系列广播连接的mapreduce分布式矩阵分解

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507195

Sebastian Schelter, Christoph Boden, M. Schenck, Alexander B. Alexandrov, V. Markl

引用次数: 54

Beyond rating prediction accuracy: on new perspectives in recommender systems 超越评级预测的准确性:推荐系统的新视角

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2508073

Panagiotis Adamopoulos

引用次数: 34

When power users attack: assessing impacts in collaborative recommender systems 当高级用户攻击:评估协作推荐系统的影响

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507220

David C. Wilson, C. E. Seminario

{"title":"When power users attack: assessing impacts in collaborative recommender systems","authors":"David C. Wilson, C. E. Seminario","doi":"10.1145/2507157.2507220","DOIUrl":"https://doi.org/10.1145/2507157.2507220","url":null,"abstract":"Power users, in a Collaborative Filtering (CF) Recommender System (RS) context, are those who can exert considerable influence over the recommendation outcomes presented to other users. RS operators encourage the existence of power user communities and leverage them to help fellow users make informed purchase decisions. Thus, RS research in this area has focused on power user identification and utilization to address challenges such as rating sparsity for new items or users. But, as ever, there remains the potential for corruption of power. Alongside accuracy and efficiency measures, RS robustness to manipulation or 'attack' has been studied using injection of false user profiles. Our research is investigating the impact on RS predictions and top-N recommendation lists when simulated power users provide biased ratings for new items. In this study, we introduce the notion of a 'Power User Attack' for RS robustness analysis, as well as a novel use of social networking degree centrality concepts for identifying RS power users. Initial results show that power users identified using in-degree centrality, compared to other techniques, can be more influential as reflected by accuracy and robustness impacts before and after power user attacks.","PeriodicalId":225573,"journal":{"name":"Proceedings of the 7th ACM conference on Recommender systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124246333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 30

Not by search alone: how recommendations complement search results 不仅仅是通过搜索:推荐如何补充搜索结果

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507231

Daria Dzyabura, A. Tuzhilin

引用次数: 2

Sentimental product recommendation 感性产品推荐

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507199

Ruihai Dong, Michael P. O'Mahony, M. Schaal, Kevin McCarthy, B. Smyth

引用次数: 54

Learning to rank for recommender systems 学习为推荐系统排序

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2508063

Alexandros Karatzoglou, L. Baltrunas, Yue Shi

引用次数: 126

Leveraging the citation graph to recommend keywords 利用引文图来推荐关键词

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507197

I. Blank, L. Rokach, Guy Shani

引用次数: 11

Towards scalable and accurate item-oriented recommendations 向可扩展和准确的面向项目的推荐

Proceedings of the 7th ACM conference on Recommender systems Pub Date : 2013-10-12 DOI: 10.1145/2507157.2507208

Noam Koenigstein, Y. Koren

引用次数: 47