A novel approach for webpage ranking using updated content

Ganeshiya, Deepak Kumar; Sharma, Dilip Kumar

doi:10.1109/confluence.2014.6949383

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…The algorithm performed well as it considers both the weighted links popularity and user visits on the page but it did not consider the content change on the web page. (Kim et.al 2013;Ganeshiya et al 2014) used the concept of web structure and web content mining to evaluate the relevance of page with respect to user query. The technique finds the cosine similarity between the user query and the updated content of the web page.…”

Section: W Y X Imentioning

confidence: 99%

An Automatic User Interest Mining Technique for Retrieving Quality Data

Sethi

Dixit

2017

International Journal of Business Analytics

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Search engines acts as an intermediate between the user and web. It takes the user query as input and retrieves the pages based on query terms from its database, which is in advance populated from World Wide Web. It then applies some ranking algorithm to sort the retrieved pages and presents the results back to the user in the form of millions of web pages. But most of pages in the result are not useful to the user. This problem arises because the search engine retrieves the results based on query keywords only and no attention is paid in incorporating the user interest during the ranking process. Due to the lack of automatic mechanism for tracking user browsing patterns, user seldom gets the relevant results in the top ten links. So, in order to cater the need of individual user, an automatic user interest mining technique for retrieving quality data is being proposed here. The mechanism provides the satisfactory results to the user as each user interest is maintained separately without any hassle at the user end.

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Section: W Y X Imentioning

confidence: 99%