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Tourism Destination Recommender System for the Cold Start Problem
( Xiaoyao Zheng ),( Yonglong Luo ),( Zhiyun Xu ),( Qingying Yu ),( Lin Lu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.7
With the advent and popularity of e-commerce, an increasing number of consumers prefer to order tourism products online. A recommender system can help these users contend with information overload; however, such a system is affected by the cold start problem. Online tourism destination searching is a more difficult task than others on account of its more restrictive factors. In this paper, we therefore propose a tourism destination recommender system that employs opinion-mining technology to refine user preferences and item opinion reputations. These elements are then fused into a hybrid collaborative filtering method by combining user- and item-based collaborative filtering approaches. Meanwhile, we embed an artificial interactive module in our recommender system to alleviate the cold start problem. Compared with several well-known cold start recommendation approaches, our method provides improved recommendation accuracy and quality. A series of experimental evaluations using a publicly available dataset demonstrate that the proposed recommender system outperforms existing recommender systems in addressing the cold start problem.
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Multi-Tenant Data Storage Model and Performance Evaluation
Dun Li,Zhenfei Wang,Zhiyun Zheng,Jin Zhao 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.3
Multi-tenant data storage model has multiple solutions and comparing the different storage solutions can help users improve their work efficiency. This paper proposes a query performance evaluation method based on the relational algebra. First of all, we introduce three wide table models. Secondly, we unite the format of tenant query SQL statement by analyzing structure of storage model, replace the unified format SQL with the relational algebra and evaluate the I/O cost of SQL query using relational algebra. Finally, through theoretical calculations and experimental simulations, we evaluate the performance of multi-tenant storage model according to query performance. The results show our evaluation method based on relational algebra provides new perspective for the study of performance evaluation in multi-tenant data model.
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Wang Qi,Dai Huajie,Hou Tianzhichao,Hou Yanan,Wang Tiange,Lin Hong,Zhao Zhiyun,Li Mian,Zheng Ruizhi,Wang Shuangyuan,Lu Jieli,Xu Yu,Liu Ruixin,Ning Guang,Wang Weiqing,Bi Yufang,Zheng Jie,Xu Min 대한뇌졸중학회 2023 Journal of stroke Vol.25 No.3
Background and Purpose We investigated the causal relationships between the gut microbiota (GM), stroke, and potential metabolite mediators using Mendelian randomization (MR). Methods We leveraged the summary statistics of GM (n=18,340 in the MiBioGen consortium), blood metabolites (n=115,078 in the UK Biobank), and stroke (cases n=60,176 and controls n=1,310,725 in the Global Biobank Meta-Analysis Initiative) from the largest genome-wide association studies to date. We performed bidirectional MR analyses to explore the causal relationships between the GM and stroke, and two mediation analyses, two-step MR and multivariable MR, to discover potential mediating metabolites. Results Ten taxa were causally associated with stroke, and stroke led to changes in 27 taxa. In the two-step MR, <i>Bifidobacteriales</i> order, <i>Bifidobacteriaceae</i> family, <i>Desulfovibrio</i> genus, apolipoprotein A1 (ApoA1), phospholipids in high-density lipoprotein (HDL_PL), and the ratio of apolipoprotein B to ApoA1 (ApoB/ApoA1) were causally associated with stroke (all <i>P</i><0.044). The causal associations between <i>Bifidobacteriales</i> order, <i>Bifidobacteriaceae</i> family and stroke were validated using the weighted median method in an independent cohort. The three GM taxa were all positively associated with ApoA1 and HDL_PL, whereas <i>Desulfovibrio</i> genus was negatively associated with ApoB/ApoA1 (all <i>P</i><0.010). Additionally, the causal associations between the three GM taxa and ApoA1 remained significant after correcting for the false discovery rate (all q-values <0.027). Multivariable MR showed that the associations between <i>Bifidobacteriales</i> order, <i>Bifidobacteriaceae</i> family and stroke were mediated by ApoA1 and HDL_PL, each accounting for 6.5% (<i>P</i>=0.028) and 4.6% (<i>P</i>=0.033); the association between <i>Desulfovibrio</i> genus and stroke was mediated by ApoA1, HDL_PL, and ApoB/ApoA1, with mediated proportions of 7.6% (<i>P</i>=0.019), 4.2% (<i>P</i>=0.035), and 9.1% (<i>P</i>=0.013), respectively. Conclusion The current MR study provides evidence supporting the causal relationships between several specific GM taxa and stroke and potential mediating metabolites.
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