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Getting Bulk Data Through Google: An empirical study
Author(s) -
Shama Rani,
Jaiteg Singh
Publication year - 2016
Publication title -
journal of technology management for growing economies
Language(s) - English
Resource type - Journals
eISSN - 2456-3226
pISSN - 0976-545X
DOI - 10.15415/jtmge.2016.72002
Subject(s) - computer science , information retrieval , search engine , database , web search engine , search oriented architecture , metasearch engine , index (typography) , world wide web , matching (statistics) , inverted index , web search query , search engine indexing , statistics , mathematics
To store the information in a database is one of the major tasks. The efficient storage of data is important for future use. Information retrieval is a method of gathering information related to input queries from the various sources or stored databases. To retrieve the information, a search engine plays an important role. A web search engine creates an index to match queries. The quality of information is improved with the help of search engine. For retrieving the information, a search engine comprises some modules such as query processor, a searching and matching function, document processor and page rank capability. This paper focuses on the retrieval of web documents against input queries and stores them in to database. A Google search API can be used to fetch the results. It analyses the data by processing through these modules and downloads the content available in different formats.

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