The Study On Search Strategy And Algorithm Design Of Theme Search Engine

Site search in the Internet application is becoming more and more popular,a web site to become bigger and stronger,is bound to enrich its content,the user wants to find content,whether new or old(such as a long time ago the user saw a news reports,because no longer is the latest content and does not appear on the front page),we can use search engines to find it.By search engine,users can enjoy to get the resources fast service,almost never leave home,search engine can make people more effectively obtain all kinds of information from Internet,so the good or bad of a search engine directly determines the people's Internet life.This paper analyzes the main search strategies and algorithms,and analyzes the classification,technical structure and principle structure of the search engine,at the same time,based on design of theme crawler system are studied and the model is established,integrating machine learning algorithms with existing technical support,the paper discusses the characteristics of the document,the current mainstream tf-idf improvement algorithm is also described,with Python 2.7 as the development platform,the theme crawler system based on the Context Graph was designed.Finally in the domestic each big automobile website,for example,set give priority to "auto" inscription to crawl classification,to recall,precision and F1 value to evaluate the performance of the system involved.The results show that the algorithm of this paper has better performance in the classification of subject words and the efficiency of web page climbing.