Hybrid crawling for time-based personalized web search ranking
Foram S. Manek, A. Jitheesh Kumar Reddy, Vaibhavi Panchal, Vijaya U. Pinjarkar · 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA) · 2017
We are leaving in the age of global interconnectivity where internet and related communication technology reign supreme and has taken a place of basic necessity in business as well as daily routine. Internet has become the largest source of information available on the planet. Its importance has been increased extensively because of search engines. Search Engine tools help us to find data on the web rapidly. Many a times the available data is irrelevant to the user's actual needs. The users need efficient search tool to find the relevant data. So continuous efforts are made to improve its accuracy but are still satisfactory. Thus, the designation of efficient and optimum search engine is needed to surmount our problem of relevancy. We aim on ranking algorithms to provide methodology for combining this algorithm to produce more relevantly ranked results. Re-ranking is the new approach which is also present to produce relevant and filtered ranked results for improving user's goals and needs. The content based ranking is based on contents and keywords rather than link structure and keywords provided by search engines. Search engines results are retrieved based on the user query. Also, usage based ranking algorithm consider the past user navigation pattern and analyze the behavior of user to recommend the data. The personalization provides content and services based on the knowledge about an individual's preferences and behavior. The motivation for this personalization is boosted by the attempt to provide results, which not only satisfy the submitted query but also the user's information needs.