KEYWORDS: Data storage, Internet, Technology, Picosecond phenomena, Data processing, Data modeling, Tunable filters, Systems modeling, Statistical analysis, Lithium
With the rapid development of Internet and the increasing amount of information, it is necessary to use big data technology to solve the bottleneck of processing speed and storage of traditional public opinion monitoring in the era of big data. In this paper, Hadoop open source platform is used to build a big data foundation, realize distributed storage of data, use MapReduce and Spark to realize distributed computing and processing of data, and process the collected data in text. The algorithm model is used to classify and cluster the text information to complete the analysis of text emotional tendency, topic discovery and tracking, and innovatively grasp the public opinion information status of network emergencies. The experimental results from the acquisition rate and average correlation test prove that the algorithm in this paper has higher calculation accuracy. It can provide real-time and effective public opinion analysis service.
KEYWORDS: Power supplies, Fuzzy logic, Neural networks, Lithium, Emotion, Design and modelling, Visualization, Signal analyzers, Internet, Information technology
To improve the accuracy of the power supply enterprise service network public opinion crisis early warning, the fuzzy reasoning theory is introduced to carry out the design research of the power supply enterprise service network public opinion early warning method. Based on public opinion topic intensity, development heat and public attitude, the power supply enterprise service network public opinion early warning index system is constructed. Combined with fuzzy reasoning theory, the index membership degree and early warning level membership degree are calculated. Through the learning method, the public opinion early warning level judgment rule is learned, and the public opinion early warning level judgment and early warning display are completed. The experiment proves that the new public opinion early warning method can accurately judge the degree of public opinion crisis, and give a reasonable and intuitive early warning display result.
KEYWORDS: Power supplies, Analytical research, Error analysis, Data processing, Data modeling, Data conversion, Databases, Standards development, Lithium, Fuzzy logic
To improve the response time of public opinion on early warning of power service and expand the coverage of early warning, this time, combined with the theme of web crawler technology, the research on public opinion on early warning technology of power supply service is carried out. According to the power service situation, collect the public opinion data of power supply service, analyze the public opinion situation according to the service results, and conduct topic discovery. Based on this, the overlapping web crawler public opinion early warning model is designed, and the public opinion threat estimation method is used to realize early warning processing. The final test results show that: Compared with the traditional clustering public opinion early warning test group and the traditional sentiment calculation public opinion early warning test group, the final early warning response time of the theme web crawler public opinion early warning test group designed in this paper is controlled within 1.5s. It shows that in the practical application process, the method in this paper has a fast early warning speed for public opinion, and the error of data and information processing is small, which has practical application value.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.