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The Research of Stock Information Search and Prediction System Based on Mobile Platform

Author: ZuoWenDa
Tutor: LiPeng
School: Harbin University of Science and Technology
Course: Applied Computer Technology
Keywords: vertical search engine sentiment classification Bayesian classification algorithm system similarity model Android
CLC: TP393.09
Type: Master's thesis
Year: 2011
Downloads: 44
Quote: 0
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Abstract


Internet has become an important way for people to obtain information with the rapid development of internet in worldwide. However, it becomes extremely difficult for us to obtain the useful information with the huge growth of internet information. Search engine plays an important role in information retrieval. It has been an indispensable tool for information retrieval in our daily life. As the networks become more complex, even Google, Baidu and other search engine can not fully meet the needs of users. The vertical search engine faced specialized field becomes a research hotspot of search.Internet is an interactive media and more and more people use it to express their views and attitudes. How to use the stock information which has the subjectivity of language preference to predict future stock price movement becomes a research hotspot of Sentiment Classification. Sentiment Classification belongs to natural language processing and its main aim is to obtain the subjective appraisal tend implied in the text and predicts the future trends. The rapid development of wireless communications causes a substantial increase in demand for smart phones. In the 3G era, the function of mobile phones becomes more and more prefect and the tariff will come down. Android phones occupy the market quickly because of their irreplaceable opening and flexibility.This article describes the technology of web data acquisition, sentiment classification and mobile platform. We improve the traditional data acquisition technology of search engine for the characteristics of stock information. We design focused web crawler face stock information of financial field through the strategy of combining artificial neural network with Shark-search algorithm to guide the direction of web crawler system. We design and implement focused web crawler face stock information of financial field. At the same time, we propose a method based on symbol to judge whether the web pages are the same. This method can well solve the problem of duplicate web pages. And we improve the system similarity model and design a stock information analysis and forecast system based on Bayesian classification algorithm and system similarity model.Finally, we implement a stock information search and prediction system in the android platform. This system collects stock information of internet automatically. It predicts future price movements of stock plate through processing and analysis the stock information.

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