Abstract: a string similarity measure or similarity function calculation is a main operation in web search engine. The operation of string metric calculation is the main part that can be used to identify similarity between two text strings. For appropriate string similarity calculation, there are various kinds of technologies has been introduced. In recent years, the efficient string similarity measure operations were done with the processing concept of inverted indexes. The filter and refine techniques is the main operation for identifying and verifying similar strings in the given data collection. For large volume of data, the computation cost will be high. A prefix based inverted index has been calculated for relevant query extraction. Based upon the prefix value, the approach of multiple prefix filtering can be used to produce most similar string. In this paper, we propose a Q-gram based edit distance metric for efficient string similarity operation. For approximate string matching, Q-gram distance is a very effective and widely used distance metric. And FP-growth algorithm can be used for user query recommendation which makes effective query processing system.
Keywords: prefix filtering, Q-gram edit distance metric, FP-growth algorithm, information retrieval.
Title: Efficient Query Processing System on Web Search Engine
Author: K.Bhuvaneswari, G.Sudhakhar
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Research Publish Journals
