A Research And Application In Improved Boyer-Moore Algorithm

As our country promote the new policy "Internet +", the Internet will become an indispensable part of our study and life. At present colleges graduation thesis topic selection, mainly uses the artificial way. In this way, teachers and student’s work will become complicated and low efficiency from topic to topic selection and the subsequent series of complicated work. Based on the above reasons, developed an online graduation thesis topic selection system. The online graduation thesis topic selection system has three module:teacher module, student module and administrator module. Teachers can log on the online graduation thesis topic selection system to publish paper topic and topic introduces; Students can log in the system to choose paper topics which suit themselves, search module can help student find the literature after choosing their paper topic; Administrator can log in the system and edit person’s file, import or output the topic information.In order to help student to choose their paper topics. The intelligent paper literature search module will provide the function. In this module, search the references function has become the core technology. The study found that Boyer Moore algorithm has not appropriate jump distance which in the large number of text matching, cause the algorithm was inefficiency.The original "good suffix rules" and "bad character rule" improved to calculate the bad character and the character after the bad character’s jump distance, and then take the max value of them. After improving the algorithm, reducing the number of matching and increasing the efficiency. Especially the matching of Chinese characters, providing the feasible and efficiency optimization scheme in the environment of big data.Design the experiment of Boyer-Moore algorithm, Boyer-Moore Horspool algorithm and improved Boyer-Moore algorithm. The experimental results show that the improved algorithm improves the matching efficiency.