Keyword search method of distributed file in large data environment

ABSTRACT

Improvements are made to a kind of effective search method of big data. When the query request arrives, analyze the user’s query request intention, provide the keywords for the user to select, segment the keywords after determining the keywords finally used by the user, and extract the thematic words and auxiliary words. This paper improves such search method of big data. When the new query request arrives, firstly analyze the user’s query request intention, provide the keywords for the user to select, segment the keywords after determining the keywords finally used by the user, and extract the thematic words and auxiliary words. Make classification matching for the thematic words and historical query, and combine the shared historical query result and query result of a new date after matching. If there is the auxiliary word, take the historical query result as the intermediate result set, continue query on this basis; if there is no auxiliary word, directly take the combination as the query result. The improved search method saves the search time better and improves the query efficiency.

KEYWORDS:

• Big data
• search
• query network
• cloud database

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Hu Xinxin

Hu Xinxin is associated with the College of Civil Engineering and Architecture in Neijiang Normal University at Neijiang, China. He has done lot of research works in the area of civil and architecture. He works specifically on computer applications of civil sense in big data.

Liang Fengshou

Liang Fengshou is associated with the Automotive Engineering Research Institute, BYD Auto Industry Company Limited at Shenzhen, China. He has published several research articles in automotive engineering. He has been in collaboration with various researchers. He has been guiding research for many of his students.