Research And Implementation Of Personalized Politics Information Search Engine

With the current rapid development of computer technology of our societyandvarious data network explosion, the era of big data has been coming. In face of such matter, GOOGLE,BAIDU and other search engine was born, and grew rapidly into the world's top Internet companies, this is because that they meet the needs of most Internet users, conforming to the development of the times. But in the moment, the amount of data is growing exponentially, and the user has more demand of data acquisition. They asked the search engine to provide more accurate results matching for their anticipation in a shorter time.Therefore the ordinarysearch Engine is far beyond such requirements; we need to design an improved search engine to adapt to the user needs, precise, fast, and seasonal oriented.Currently there are many technologies for such demand, such as vertical search technology,personalization technology. Vertical search technology can help users deeply explore in their own fields of expertise with more efficient and accurate search. Personalization technology refers to that developing a searchingprogram for each user meeting his demand.By this "Personal Tailor ', it can greatly improve user‘ssatisfaction of search results. So a search engine added in the personalization technology and vertical search technology is consistent with the needs of the current time, it is necessary to study that. The most important now is the campaign of e-government network construction vigorously promoted by the party and government departments.This paper ofresearch in personalized information searchof current affairs willplay a big role in the coming e-government network applications.This dissertation analyzes the current status of the development of countries in search engine technology, introducing users' new requirement of search enginein the era of big data, and has a detaileddescription on key parts of universal search engine functions and principles, such as web crawlers, web sorting, indexing mechanism. Then through the study concept, the basic principle, and composition of vertical search engine,analyzingits web crawler, keyword search, index and other important modules, and finally creating a user interest model, applying those all in ordinary search engine in order to design a search engine satisfying vertical and personalized search need, which will be expressed by PPISE.The main role of the network crawler is crawling data module website, and has URL filtering ofthese relevant data; retrieval module is mainly combining text classification technology and user interest model together to improve relevance between search results and user needs; indexing module is mainly classifying different texts in the indexing according to the user's interests, etc., it uses text classification technology, and to ensure the efficiency index.In this dissertation, there are three aspects of the study design, with improvement and innovation in some extent: Firstlyit brings the introduction of the URL relevant filtering mechanism in web crawlers to improve situation that the current search engines fails to filter out irrelevant noise page,reducing unnecessary crawling by filtering out a lot of irrelevant pages to keep information gathering efficiency. Secondly, it designs of a text classification method, which joined with the improved feature selection function, text categorization technology. It makes personalized search engine classification of the text more detailed and accurate, also more in line with the individual needs of users. Thirdly, it designs a model of user interest, improved by he relevant feedback technology, to enhance the ability of the search to personalize.