Dataset Information

Empirical Study of User Preferences Based on Rating Data of Movies.

ABSTRACT: User preference plays a prominent role in many fields, including electronic commerce, social opinion, and Internet search engines. Particularly in recommender systems, it directly influences the accuracy of the recommendation. Though many methods have been presented, most of these have only focused on how to improve the recommendation results. In this paper, we introduce an empirical study of user preferences based on a set of rating data about movies. We develop a simple statistical method to investigate the characteristics of user preferences. We find that the movies have potential characteristics of closure, which results in the formation of numerous cliques with a power-law size distribution. We also find that a user related to a small clique always has similar opinions on the movies in this clique. Then, we suggest a user preference model, which can eliminate the predictions that are considered to be impracticable. Numerical results show that the model can reflect user preference with remarkable accuracy when data elimination is allowed, and random factors in the rating data make prediction error inevitable. In further research, we will investigate many other rating data sets to examine the universality of our findings.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC4703247 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Empirical Study of User Preferences Based on Rating Data of Movies.

Zhao YingSi Y Shen Bo B

PloS one 20160106 1

User preference plays a prominent role in many fields, including electronic commerce, social opinion, and Internet search engines. Particularly in recommender systems, it directly influences the accuracy of the recommendation. Though many methods have been presented, most of these have only focused on how to improve the recommendation results. In this paper, we introduce an empirical study of user preferences based on a set of rating data about movies. We develop a simple statistical method to i ...[more]

PMID: 26735847

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Project description:BackgroundOver the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being.ObjectiveThis paper presents an Artificial Intelligence (AI)-enabled mHealth app rating tool, called ACCU3RATE, which takes multidimensional measures such as user star rating, user review and features declared by the developer to generate the rating of an app. However, currently, there is very little conceptual understanding on how user reviews affect app rating from a multi-dimensional perspective. This study applies AI-based text mining technique to develop more comprehensive understanding of user feedback based on several important factors, determining the mHealth app ratings.MethodBased on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user star rating, user text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users' sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer's statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score.Results and conclusionsACCU3RATE concentrates on heart related Apps found in the play store and App gallery. The findings indicate the efficacy of the proposed method as opposed to the current device scale. This study has implications for both App developers and consumers who are using mHealth Apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has also been noticed that the fuzzy based rating scale, as in ACCU3RATE, matches more closely to the rating performed by experts.

Project description:Insecticide-treated bed nets (ITNs) are the primary tool for vector control, and optimizing ITN use is a key concern of national programmes. Available evidence indicates that bed net users often have preferences for shape, colour, size, and other attributes, but it is unclear whether these preferences are strong enough to have any significant effect on bed net use, and whether countries and donors should invest in more expensive attributes in order to maximize ITN use. The link between bed net attributes, preferences, and use was investigated using a literature review and review of publicly available, nationally representative household surveys from sub-Saharan Africa.A literature search was conducted to identify publications with data on preferences for net attributes and on associations between net attributes and use. Publicly available DHS and MIS datasets were screened for variables on net preferences and net attributes. Wald tests were run to obtain odds ratios and confidence intervals for the use of nets of various attributes in univariate analysis. A multilevel logistic regression was constructed to assess the odds of a net's use, controlling for background variables and adding random effects variables at the household and cluster level.Preferences for certain net attributes exist, but do not impede high rates of net use in countries where data were available. Stated preferences for shape and colour do not significantly influence net use to degrees that would require action by programme planners. By and large, people are using the nets they receive, and when they do not, it is for reasons unrelated to shape and size (primarily perceived mosquito density, heat or an excess of nets). Households in higher wealth quintiles tend to own greater numbers of conical nets, indicating that they have the ability to obtain or purchase these nets on their own, and individuals resident in higher wealth quintile households also use conical nets preferentially.The increased manufacturing costs for conical nets are not outweighed by the very small, often non-existent, increases in use rates in sub-Saharan Africa. Programmes that wish to explore the relationship between net attributes, preferences and use rates should include these questions in nationally representative household surveys to be able to capture trends across geographic and socio-economic groups.

Dataset Information

Empirical Study of User Preferences Based on Rating Data of Movies.

Publications

Empirical Study of User Preferences Based on Rating Data of Movies.

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