@article{MAKHILLIJSC201712521426,
    title = {An Improved Web Emotion Analysis using Hybrid PAM Neural Network Approach},
    journal = {International Journal of Soft Computing},
    volume = {12},
    number = {5},
    pages = {303-307},
    year = {2017},
    issn = {1816-9503},
    doi = {ijscomp.2017.303.307},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2017.303.307},
    author = {Meera and},
    keywords = {CPU,access patterns,clustering,techniques,integrating,efficiently,accuracy},
    abstract = {Web usage mining method for learning episodic web access patterns from web usage logs which
integrates knowledge on customer’s interest and behaviours. A novel method to efficiently provide
better web-page recommendation through semantic-enhancement by integrating the domain and web usage
knowledge of a website is introduced in this study. Here, we propose, a hybrid approach by first enriching the
contextual information by k-medoids algorithm and training each cluster using simple Neural Network approach.
This method improves the cluster quality in term of accuracy and CPU time when compared to traditional
clustering techniques like k-means clustering and deterministic genetic clustering techniques.}
    }