alexa Recommendation on the Web Search by Using Co-Occurrence
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Research Article

Recommendation on the Web Search by Using Co-Occurrence

S.Jayabalaji1, G.Thilagavathy1, P.Kubendiran1, V.D.Srihari2
  1. UG Scholar, Department of Computer science & Engineering, Sree Shakthi Engineering College, Coimbatore, Tamilnadu, India
  2. Assistant Professor, Department of Computer science & Engineering, Sree Shakthi Engineering College, Coimbatore, Tamilnadu, India
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Abstract

In our day to day, the usage of internet and searching the information should be increases rapidly. Because of this, now a days we have facing the problems like whether the retrieving information would be noise free or not and having many confusions with the usage of keywords to get the exact result. To avoid this problem we are going to propose the concepts called Co-Occurrence and recommendation. These two concepts increases the effectiveness and of the result. By using the recommendation concept we have multiple choices to select the desired thing. The web search increases dramatically [1] user search performance leads to large number of confusions. We examine a general expert search problem: searching experts on the web, where millions of web pages and thousands of names are considered. The two main issues are: Web pages might be of untrustworthy and have more noise; the knowledge evidences spotted in web pages are frequently unclear and ambiguous. The skilled search has been studied in different contexts, e.g., enterprises, academic communities. We propose to influence the huge quantity of co-occurrence information to calculate the significance and status of a person name for a query which is given. So this makes the recommendation system the most important and the trust worthiness of the system will be analyzed in the better way. The personalization will be depended based on the individual user process in the web search mainly worked in E-Commerce application.

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