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Enhancing Privacy Search in Web Search Engine Using Greedy Algorithm
| Content Provider | Semantic Scholar |
|---|---|
| Author | Sumathi, N. Karuppuchamy, Veeramani |
| Copyright Year | 2015 |
| Abstract | In web search, there are many techniques used extensively for effective retrieval of information from the web server. A user query entered into the search engine may return large number of web page results and thus, it becomes extremely important to rank these results in such a manner that it returns accurate and more relevant web results. These tasks of prioritizing the results are performed by ranking algorithms. But the search interest of every user differs with every other user uniquely. In existing system, the search engine that return results for a given user query is not uniquely based on their earlier searching behavior. Hence there may be return of web page results that are least used or accessed by the user. These results need to be filtered or less prioritized by the ranking algorithm. In our proposed system, the personalization of user search activities is taken to find search interest of each user. This personalization of user search behavior is done by storing user activities and analyzing web log by clustering frequently accessed tasks by semantic task clustering algorithm and dynamically ranks web results. In this project we can also extend our work include web image search with personalization and remove duplication keywords. It can be achieved using image features approach and top k answering techniques. Implement this approach in real time search engine environment. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijirset.com/upload/2015/multicon/cse/51_ICCTS248_NEW.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
