Research On Big Data And Its Countermeasures

In today's society,the Internet is rapidly developing,so Internet merchants can use the user information they have mastered to analyze consumer preferences.Then they conduct product recommendations to maximize profits.The accumulation of data on the behavior of consumers browsing,purchasing,and viewing advertisements on the Internet has become the basic source of information used by Internet companies to analyze users.Although these behaviors bring a lot of convenience,its negative impact can not be ignored,that is,"big data kills." At present,it is very common for consumers to use mobile phone software for business activities.In particular,the software usage rate of shopping and living services currently has a very high proportion,and big data “killing” is hidden in the mobile phone software commonly used by consumers.There are a lot of big data "killing" behaviors in the behaviors related to life,such as the reservation of hotel rooms and airline tickets,the purchase of taxis and movie tickets.The Internet merchant platform uses the behavioral preference data of the users that have been mastered before to analyze the different usage habits of users of different consumption levels and their usage requirements.Older users who are more dependent on Internet applications are offered higherpriced goods or services.Conversely,the price of the goods or services offered is relatively low,and the pricing of different consumers is finally differentiated.At present,the discussion of the phenomenon of “killing” big data in academia and the media is mainly focused on price differential pricing.However,combined with the characteristics of e-commerce,it can be found that this kind of killing phenomenon is not only reflected in the price differential pricing,but the quality difference and service difference on the same price basis may become the target of the merchant platform.The main contributions of this dissertation are as follows:(1)Research on big data killing against technology: This dissertation studies in detail how to use existing technology to combat big data “killing” phenomenon;Internet business companies prefer privacy by different means of mobile phone users,and then use their own user behavior preference data to construct user portraits for consumers,and finally recommend products or services through the user's portrait without the consumer's knowledge.Based on this,the research objectives and specific work of the article are summarized in detail.This part first studied Web related technologies and Python programming languages.Based on Web services,the Python language's concise,easy-to-use features and its rich third-party libraries provide technical support for system development and functional implementation.Then we analyze the common framework in the Python programming language and compare it with the common Java framework.It is found that the Django framework in the Python language has a fully automated management background.The application to the system can make the development more convenient.Finally,we studied the web crawler technology,using the simple crawler code to crawl and save the information of the group purchase website as the data source of the system.Combining the advantages of Python in system development and data processing,the ultimate big data killing system is implemented.(2)Design and implementation of big data killing system: This dissertation designs and implements a big data killing system based on Python language.The killing system can replace consumers to buy goods or services,mainly realizes the following functions: data acquisition and filtering,user login function,product search function,product order function,automatic clearing of cookies and random browsing and simulation of orders.The system crawls the website product information and pre-processes it,and then searches for the user.The system replaces the consumer to purchase the product,so that the Internet platform cannot directly access the user's information.Then,by randomly browsing and simulating the operation of the order,the platform collects the data collection of the user's browsing record and the purchase record,and then clears the cached cookie information after the user quits.Through this series of operations,the Internet platform cannot obtain accurate information.The fuzzy Internet platform builds the consumer user portrait to achieve the goal of combating big data.