BibTeX:

@article{IJIRSTV2I2034,
     title={A New Dimensional Knowledge Discovery for Routing Network using Latent Feature Model},
     author={Emil George and Silja Varghese},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={2},
     pages={202--206},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I2034.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Cyber Physical Systems are primarily focused to interact with other systems across the data collection. Information collection depends on the field of knowledge discovery. This contains information either from field based or collaborative filtering. In a domain recommendation model, filtering data based on the rating pattern across the domains. The basic functionality of the cross domain recommendation model is to seek and retrieve the information with reduced the repeated records. A domain recommendation model, which are identifying the common routing pattern across specific domains and determining the specific domain rating patterns in each domain containing similar behavior and relation which exists among the fields. For the clustering information, system utilizing a different data set with an additional amount of accumulating data. These data sets are compared and filtered with items and are clustered with domains. The clustering process reduces the uncompleted data sets and offers more meaningful data. Domain recommendation model mainly integrating the knowledge discovery and information transport as part of the information transfer organization. The major type of systems is offered retrievals of items through the single field. The cross domain recommendation provides data by integrating multiple areas with identical details.

Cyber Physical System, Cross Domain Recommendation, Nonnegative Matrix Factorization, Knowledge Discovery and Information Retrieval