Due to the exponential growth of Internet users and traffic, information seekers depend
highly on search engines to extract relevant information. Due to the accessibility of a large …

Search engines are very useful tool now a days to fulfill the information need of a user. The
performance of search engine mainly depends on page ranking algorithm which provides …

Current research in automatic train operation concentrates on optimizing an energy-efficient
speed profile and designing control algorithms to track the speed profile, which may reduce …

The Tor network hosts a significant amount of hidden services related to suspicious
activities. Law Enforcement Agencies need to monitor and to investigate crimes hidden …

Purpose–The purpose of this paper is to estimate Google search engine's ranking function
from a search engine optimization (SEO) perspective. Design/methodology/approach–The …

We investigate whether quantum annealers with select chip layouts can outperform classical
computers in reinforcement learning tasks. We associate a transverse field Ising spin …

Learning to rank is an increasingly important scientific field that comprises the use of
machine learning for the ranking task. New learning to rank methods are generally …

This study presents a review of search engines and search engine optimization and shows
how the search engine landscape relates to sustainable development. We have used a …

This paper proposes a new, novel ranking method called Inverse-Reinforcement Learning
Ranking. The main goal is to find a reward function representing the user's perceived utility …

Rank aggregation is a task of combining individual rankings into a consensus, which has
widespread applications in many areas, ranging from social choice to information retrieval …