A trust prediction model for service web

We propose a trust prediction model for service Web using the Hidden Markov Model (HMM). The proposed model uses a dynamic training scheme that incorporates temporal sensitivity by using a dynamic training pool. The concept of the dynamically updated training pool enables the system to absorb newest information from data. We present the implementation of the proposed model and corresponding algorithm and their evaluation on real life data.