Weixing Huang

Public Cultural Big Data Analysis Platform

Public cultural services are developed rapidly. The growth of the data related to the public cultural services are dramatically. It needs big data technologies for processing the massive public cultural data. This paper proposes a big data analysis platform for facilitating the public cultural services. The platform collects cultural data from public cultural institutions and analyzes the data by cultural model-based algorithms. The platform architecture is introduced in the paper which is based on standard Cloud Computing platform and Hadoop ecosystem. Applications for the platform are presented in the paper. By the platform public culture consumers can obtain much more valuable information.

TopicPie: An Interactive Visualization for LDA-Based Topic Analysis

LDA-based topic analysis is widely used in text mining field. Considering the large scale of web documents, document clusters are usually analyzed instead of single ones. However, the existing visualizations of LDA-based clustering do not intuitively present contents of hot topics while maintaining the relationships between the topics and the document clusters. In this paper, we propose an integrated interactive visualization method that provides intuitive and effective views for topic popularity, topic contents, document clusters, and relationships between topics and document clusters. In this way, users can quickly identify the topic-based patterns. We show an experimental evaluation by comparing the tabular representation and our visualization. The results show that our method can significantly facilitate the topic analysis, particularly in the field of Chinese culture study.

Big Data Collection and Analysis Framework Research for Public Digital Culture Sharing Service

The big data collection and analysis of public digital culture sharing service is researched in this paper. Big data includes three types of data, namely: ancillary service data, public digital culture sharing service platform operation data and user data. The aim is to build a data analysis platform for the three classes of data. Through the analysis of the three types of data collected, the use of resources and the operation of the platform can be mastered for providing better service for resource organization and scheduling of platform. Through the analysis of three types of the collected data, it can realize all kinds of statistics and analysis services in multidimensional. This paper presents a personalized recommender system of public digital cultural resources.

A Semantic++ MapReduce: A Preliminary Report

Big data processing is one of the hot scientific issues in the current social development. MapReduce is an important foundation for big data processing. In this paper, we propose a semantic++ MapReduce. This study includes four parts. (1) Semantic++ extraction and management for big data. We will do research about the automatically extracting, labeling and management methods for big datas semantic++ information. (2) SMRPL (Semantic++ MapReduce Programming Language). It is a declarative programming language which is close to the human thinking and be used to program for big datas applications. (3) Semantic++ MapReduce compilation methods. (4) Semantic++ MapReduce computing technology. It includes three parts. 1) Analysis of semantic++ index information of the data block, the description of the semantic++ index structure and semantic++ index information automatic loading method. 2) Analysis of all kinds of semantic++ operations such as semantic++ sorting, semantic++ grouping, semantic+++ merging and semantic++ query in the map and reduce phases. 3) Shuffle scheduling strategy based on semantic++ techniques. This papers research will optimize the MapReduce and enhance its processing efficiency and ability. Our research will provide theoretical and technological accumulation for intelligent processing of big data.

Public Cultural Services Recommendation System Architecture

Public cultural sharing service plays an important role in the public cultural platform. The recommender systems can bring users useful cultural resources and information. For safety and security reasons of the cultural resources, the external applications are not allowed to directly access the original resource data stored in the cultural databases by sending recommendation requests. The cultural recommender system needs a way to isolate the cultural resources from the outside while keeping the recommendation services. To address this issue, this paper proposes Representational State Transfer (REST)-based architecture of the cultural recommender system that can provide loosely coupled structures for system modules while maintaining the security access of the cultural resources.

A prediction method for aero-engine health management based on nonlinear time series analysis

Aero-engine is the heart of the aircraft. If a failure of aero-engine occurs during the flight, it will be a direct threat to flight safety of the aircraft, so the aero-engine health management came into being, and the prediction is a very important part of it. This paper was focused on the prediction methods of health management. Firstly, we introduced the research status of the aero-engine prediction methods, and then proposed a prediction method of nonlinear time series analysis using C-C method and BP-Adaboost algorithm, at last, a simulation example was given to illustrate the validity of the method. Experimental results indicated that the method has the advantage of high prediction precision, and to some extent, it can provide a reference for the maintenance plan.

A Study of Chinese Character Culture Big Data Platform

Chinese Characters are important elements of Chinese culture. Digitization techniques of Chinese Characters introduce attractive experiences of Chinese Character culture. The Chinese Character digitization generates large-scale data that is hard handled by traditional methods. To address this issue, in this paper, we propose Chinese Character Culture Big Data Platform that is designed based on the three-level hierarchy of cloud computing. The platform is built by means of open source technologies, for example, Hadoop ecosystem. The platform can effectively store, manage, and analyze large-scale data of digitized Chinese Character for supporting the Chinese Character culture experience application systems. This paper presents design concepts and architecture of the platform, as well as an experiment.