DATA mining is the process of revealing nontrivial, previously unknown and potentially useful information from large databases. Discovering useful patterns hidden in a database plays an essential role in several data mining tasks, such as frequent pattern mining, weighted frequent pattern mining, and high utility pattern mining. Among them, frequent pattern mining is a fundamental […]
Relative CTRs at different positions in random learning bucket
A few action-interpretation-based approaches including user segmentation, user engagement and position bias. The success of user segmentation for personalization is due to the fact that the proposed clustering algorithms actually group users by interests and preferences that are implicitly demonstrated by their behaviors. Once the interest patterns are determined by clustering algorithms, a user will […]
ONLINE LEARNING FOR PERSONALIZED RECOMMENDATION
Content optimization is defined as the problem of selecting content items to present to a user who is intent on browsing for information. There are many variants of the problem, depending on the application and the different settings where the solution is used, such as articles published on portal websites, news personalization, recommendation of dynamically […]
ONLINE LEARNING FOR PERSONALIZED RECOMMENDATION
Content optimization is defined as the problem of selecting content items to present to a user who is intent on browsing for information. There are many variants of the problem, depending on the application and the different settings where the solution is used, such as articles published on portal websites, news personalization, recommendation of dynamically […]
Finding neighboring ratings in the new relation
The internet has become an indispensable part of our lives, and it provides a platform for enterprises to deliver information about products and services to the customers conveniently. As the amount of this kind of information is increasing rapidly, one great challenge is ensuring that proper content can be delivered quickly to the appropriate customers. […]
Multiple phase division is all normalized rating Values
A novel dynamic personalized recommendation algorithm for sparse data, in which more rating data is utilized in one prediction by involving more neighboring ratings through each attribute in user and item profiles. A set of dynamic features are designed to describe the preference information based on TSA technique, and finally a recommendation is made by […]
A human behavior modeling Paradigm in cyber infrastructure
There are many problems in which one seeks to develop predictive models to map between a set of predictor variables and an outcome. Statistical tools such as multiple regression or neural networks provide mature methods for computing model parameters when the set of predictive covariates and the model structure are pre-specified. Furthermore, recent research is […]
Web-based social network to model residential electric energy Consumption
This paper introduced a new approach to social science modeling in which the participants themselves are motivated to uncover the correlates of some human behavior outcome, such as homeowner electricity usage or body mass index. In both cases participants successfully uncovered at least one statistically significant predictor of the outcome variable. For the body mass […]
Online Anomaly Detection For Practical Scenario
Outlier detection methods have been proposed for Practical Scenario. These existing approaches can be divided into three categories: distribution (statistical), distance and density-based methods. Statistical approaches assume that the data follows some standard or predetermined distributions, and this type of approach aims to find the outliers which deviate form such distributions. Most distribution models are […]
Distributed file systems are key building blocks for cloud computing applications
Cloud Computing (or cloud for short) is a compelling technology. In clouds, clients can dynamically allocate their resources on-demand without sophisticated deployment and management of resources. Key enabling technologies for clouds include the Map Reduce programming paradigm, distributed file systems, virtualization and so forth. These techniques emphasize scalability, so clouds can be large in scale, […]
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