International Journal of Engineering & Technology IJET-IJENS Vol:18 No:03 19 182303-6767-IJET-IJENS © June 2018 IJENS I J E N S Design and Development of Meta Search Engine Framework using Horizontal Partitioning Relevancy Criteria and Result Integration Factor Algorithms for Efficient Data Retrieval Sudeepthi Govathoti, Research Scholar, Andhra University, Visakhapatnam & Assistant Professor, Department of CSE, Anurag Group of Institutions, Hyderabad, India. M.S.Prasad Babu, Professor, Department of CS&SE, Andhra University, Visakhapatnam, India. Abstract— In recent years World Wide Web has tremendous growth in the volume of information that makes very difficult to locate information that is relevant to user’s interest. The search engine is the most important tool used to discover information in World Wide Web, but they are not appropriate nowadays as they do not crawl the deeper web [1]. Hence the concept of Meta search engine that is built on top of traditional search engines is adapted. This paper is aimed at the design and development of Meta search engine framework using horizontal partitioning relevancy criteria and result integration factor algorithm for efficient data retrieval. The input query given by the user gets forwarded to selected member search engines namely Google, Yahoo, and Bing. The data retrieved from member search engines are fused/merged and stored in the database. The proposed Meta Search engine framework has two core operations namely pruning and result integration. The data stored in fusion database is pruned by removing the null and irrelevant data by applying data validation and proposed “Horizontal partitioning relevancy criteria” algorithm. The pruned data is given as an input to result integration that performs re-ranking by applying result integration factor algorithm for effective display of the relevant content as per user’s interest. Index Term— Meta search engine, Fusion database, Partitioning, Page ranking, Pruning. I. OVERVIEW OF META SEARCH ENGINE The search engine is a web software program that searches for information on World Wide Web. It extracts relevant information and displays the list of results based on respective page ranking mechanism. The search engine results page (SERP) is the page displayed by a web search engine in response to a keyword query given by the user [2]. The top Web-based search engines are Google, Bing, and Yahoo. The amount of information now on the World Wide Web is overwhelming as a result it makes very difficult to locate information relevant to user’s interest using these search engines. In order to provide a solution to the above problem the concept of Meta search engine also termed as “Aggregator” came into existence [3]. The Meta search engine is a search tool that accepts input from the user and simultaneously redirects it to multiple search engines and produces its own results. The retrieved results from multiple search engines are integrated and presented to the user. Meta search engine enhances the user’s experience in retrieving information with less effort. The remaining paper is arranged as follows: In Section 2 Motivation for implementing Meta search engine, the related work and proposed work is presented in Section 3 and 4.The methodology is discussed in Section 5. The results are presented in Section 6 and the paper is concluded in Section 7. II. MOTIVATION The motivation towards implementing Meta search engine depicts that it is able to synthesize the advantages from each member search engine, and the result integration could improve the quality of searching results. The primary factors for implementing Meta search engine are listed as follows: a) Provides a broader overview of a topic searched. b) It increases the web coverage. c) Improves convenience for users. d) It provides an effective mechanism to reach the deeper web. e) Helps user to reduce the overhead of searching multiple search engines. f) It provides fast and easy access to the desired search III. RELATED WORK M.S.P.Babu et.al [4] summarized the key concept of Meta search engine that yields unique search experience for users. Dr. Naresh Kumar et.al [5] proposed MSE architecture and suggested relevancy calculation that detects more relevant results. Gurneet Kaur et.al [6] provided an overview and functioning of the search engine optimization that improves the visibility of the online business. Khattab O. Khorsheed et.al [7] proposed Message Passing Application Programming Interface (MPAPI) technique that improves the search time of search engines. Chunshuang Liu et.al [8] focused on evaluating the integration algorithms namely abstract merge algorithm, position merge algorithm. Kayalvizhi.C et.al [9] suggested approaches to handle the problem of result merging in a Meta search engine environment. Suruchi Chawla et.al [10] suggested optimization of clustered web pages that improve the effectiveness of the Personalized Web Search in a specific