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Films such as Robocop, The Matrix, and Pacific Rim have explored the possibilities of using Brain-Computer Interfaces (BCIs) to control machines with only thought. In this paper, we enhance the power of thought through a novel method of combining the powers of the brain wave, the most influential signal in the human body, and the wide range of information found on the internet during today's digital...
In recent years, more and more internet companies trend to fuse their products with personal recommendation functions. Although the idea of this business model satisfies characteristic of Internet industry felicitously, scientists and engineers gradually find out that the effect is worse than they expected. The quality of recommendation is limited by cold start, data sparse, lack of learning contextual...
We have deployed a big data platform for the insurance company. One can select the data they need from database, do data analysis job and save the final model to the model pool using the platform. We completed churn prediction task on both SPSS [1] and Spark [7] using the data providing by X insurance company and carefully compared the execution flow, runtime, model evaluation, and model precision...
Resource positioning in cloud computing system under the support of the Internet of things (IoT) is very important, especially for distributed collaborative task. Position-based services is used to collect, process, store and distribute position information. Taking a typical collaborative task - cloud manufacturing as the background, in view of resource positioning service, an algorithm supported...
Nowadays Personalized Service Collaboration (PSC) becomes more feasible due to the increasing availability of mobile application and web service. The semantic user model comprised of Resource Description Framework (RDF) plays a significant role in PSC. In practice, preferences within (personal data/model) often change with different time, context and dimension, which are dynamic information and contribute...
Scalable processing on large-scaled RDF graphs becomes a critical issue with the explosion of semantic web technologies. Most of the existing distributed RDF querying and reasoning solutions are designed based on the MapReduce paradigm. However, MapReduce should be further optimized since several inherent limitations such as lack of efficient job scheduling and iterative computing mechanisms affect...
Social recommendation plays an important role in solving the cold start problem in traditional recommender systems and improving the accuracy of recommendation results. However, it still faces serious challenges and problems due to bogus ratings or relationships injected by fake users. This practice seriously affects the authenticity of recommendation results as well as normal users' trustiness on...
QoS prediction is the most important step in web service selection and service recommendation. In the field of service computing, the most frequently method that adopted to predict the web service QoS is collaborative filtering. The existing studies usually focus on the prediction of the exact QoS values, and never prediction about its fluctuation range which is caused by the random dynamic nature...
The OWL-based Web Service ontology is one of the most important standards for semantic service composition. Performance analysis of composite service processes specified in OWL-S enables us to understand whether the process meet the SLA requirements. In this work, we propose a Petri-net-based formal framework for OWL-S processes using non-markovian-stochastic-petri-nets (NMSPN) as the intermediate...
Microblog opens a prosperous cyberspace, where people on the earth can quickly publish and receive information in a tremendously quick manner. Also different organizations including government create accounts in the microblog service in order to interact with the public society. Sina microblog service, as being the biggest Chinese microblog service player, attracts millions of users and organizations...
Sparsity Preserving Projections (SPP) is a well known approach for feature extraction and dimensionality reduction. Its success is mainly attributed to its high quality graph which is constructed by sparse representation. As an instance of graph embedding, SPP can be formulated as regression model. Thus we apply the idea of collaborative graph embedding, which reformulates SPP as a collaborative representation...
In order to improve the effect and the efficiency of the mechanical ventilation in grain storage, a context aware method is proposed. The context meta-model is defined which builds the basis for context modeling. The context model for mechanical ventilation in grain storage is built, which had full consideration of the ventilation purpose and the lifecycle of grain storage. The feasibility and the...
Semi-supervised clustering is one of the most active research area in machine learning and pattern recognition, which can improve the performance of unsupervised clustering efficiently. This paper focuses on exploiting both the label information of a few labeled samples and the spatial distribution information of large amount of unlabeled samples. We proposed a new semi-supervised clustering method,...
Social media marketing (SMM) has become an essential means of marketing in various industries, however, the attitude of financial service industry is relatively conservative. This paper explores the influencing mechanism of SMM activities on relationship marketing outcomes via relationship quality, and investigates the moderating effects of culture value on the relationships between SMM and relationship...
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