In order to choose which job field their interests and skills will place them in, students must examine capabilities discover as they progress through academics pursue the courses are most inter- ested in. As a result, be able perform better more motivated, help ideal career settle into it. Moreover, subsequent assessing possibilities in every significant region, spotters utilize this sort of v...

We revisit the basic variant of classical secretary problem. propose a new approach in which we separate between an agent (the sender) that evaluates performance and one receiver) makes hiring decision. The sender signals quality candidate to agent. Whenever two agents' interests are not fully aligned, this induces information transmission (signaling) challenge for sender. study sender's optimi...

Abstract Reading or viewing recommendations are a common feature on modern media sites. What is shown to consumers as nowadays often automatically determined by AI algorithms, typically with the goal of helping discover relevant content more easily. However, highlighting filtering information that comes such may lead undesired effects even society, for example, when an algorithm leads creation ...

One of the most difficult analyses all time is stock market predictions. Expert analysts and software engineers are collaborating to create a stable reliable platform for predicting future value. The fundamental difficulty that variety factors will influence price fluctuations. Stock recommendations vital investment firms individuals. However, no unique selection approach can capture dynamics s...

Recently the use of web recommendation techniques is growing worldwide with aim of providing the customized required data to end users. Different recommendation methods and solutions impose many research challenges to researchers. Web recommendation techniques are divided into two main types such as content based web recommendation system and collaborative web recommendation system. Basically w...

There are case-based recommender systems that generate personalized recommendations for users exploiting the knowledge contained in past recommendation cases. These systems assume that the quality of a new recommendation depends on the quality of the recorded recommendation cases. In this paper, we present a case model exploited in a mobile critique-based recommender system that generates recom...