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Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
With the development of Sina Weibo, the amount of user keeps increasing. Micro-blog “big V” users play an important role in the dissemination process of micro information. Social emergencies appeared constantly and spread on Sina Weibo, sometimes with rumors, so it is necessary to discover micro-blog “big V” users' public opinion propagation characteristics in order to set a health network environment...
With the continuous development of social networking sites, the volume of social media data has exploded and the user-generated content is becoming more and more diverse. As a result, the modality of massive social media data is no longer confined to the single text mode. This brings new challenges to social media analytics in general and its examplar field such as sentiment analysis in particular...
Online interactions, especially user generated contents on social events, reveal a variety of communicative purposes ranging from expressing feelings to proposing suggestions. Recognizing intents in users' online interactive behavior from massive social media data can effectively identify users' motives and intents behind communication and provide important information to aid monitoring, analysis...
Due to the prevalence of Multi-set high-dimensional data in the era of big data, visualization and visual analysis of multiple sets of high-dimensional data are critical to the discovery of data patterns. Parallel Coordinates Plot (PCP) is mainly used for visual analysis of different attributes of the same set. The classic method for visualization on multi-set high-dimensional data is to use a conventional...
For the phenomenon of information isolated and data redundancy between offshore platforms in ocean strategy environment, a data interaction and share scheme for multi-source heterogeneous intelligence is proposed. It adopts distributed grading share frame organizing intelligence resources share, puts forward the criterion of metadata and the define of sharing glossary data set for heterogeneous ocean...
The SVM can realize data classification and prediction, the selection of penalty parameter c and kernel function g in training models directly affect the forecasting accuracy of the classification, the article use the K-CV method for c, g parameters optimization and processing, in wine species identification as an example to predict classification, improves the forecast accuracy, has reached the expected...
Imbalanced data become an obstacle in data mining nowadays, minority class sometimes are more important than majority class, just like in medical diagnosis, credit card fraud and etc. This paper focuses on the imbalanced data problem that adaboost algorithm cannot get a proper accuracy rate for minority class, and propose an improved adaboost algorithm for imbalanced data based on weighted KNN(K-Adaboost)...
In the era of big data, the data are diverse and complex. The issue that using multi-source data efficiently in recommender system is very essential. To solve this problem, we proposes a ranking model that integrates explicit feedback data with implicit feedback data together. We use weighting factors to measure the impact of different user behaviors on recommendation quality. We solved the data fusion...
Linear mixed models are often used for analysing unbalanced data with certain missing values in a broad range of applications. The restricted maximum likelihood method is often preferred to estimate co-variance parameters in such models due to its unbiased estimation of the underlying variance parameters. The restricted log-likelihood function involves log determinants of a complicated co-variance...
Twenty-first century as an important symbol of the era of the knowledge economy and big data, Internet and networking have a rapid development and have become indispensable data sources in people's lives. Besides, because of its convenience and quickness, these are increasingly applied in more and more aspects. Among them, POI as a true representative of the geographical entity on the network map...
Although high dimensionality and heavy censoring may cause difficulties for model selection, many literatures concern the accelerated failure time (AFT) model. We perform variable selection and statistical inference for high-dimensional censoring data based on the AFT model by directly controlling the false discovery rate. We also perform some numerical simulations to evaluate the performance of the...
Domain terminology recognition and extraction is the primary work for construction of domain knowledge graph. Traditional method is tedious, and time-consuming, as well as low accuracy. This paper presents an automatic domain feature extraction method based on the Domain Feature Vectors (DFVs). Experimental results demonstrate that our approach is effectiveness and accuracy.
The paper constructs an influence model of employment structure by introducing the factor of e-business. Using monitoring data and statistical yearbook data of e-business from ten provinces of China, we conduct empirical research. The results show that e-business development prominently promotes employment. The employment effect of e-business for private enterprises and individual enterprises is greater...
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