@article{MAKHILLJEAS201712414184,
    title = {Appropriate Context for Context Aware Music Recommendation},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {4},
    pages = {840-847},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.840.847},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.840.847},
    author = {Iman and},
    keywords = {Context aware music recommendations,context information,clustering,,behavioral analysis,personalization,psychology of music inclinations,internet-based applications},
    abstract = {There are various environmental factors that impact on selection of appropriate music. For example, selection of music in a foggy mountain is totally different with music selections in traffic jam or human sensation for listening to music on a weekend morning is extremely different with a research day’s afternoon. In this study, context information which can impact on user’s choices is evaluated through psychology of music inclinations, context information used in related researches and studies and also smartphones limitations and entirely most appropriate scheme will be offered. Particularly, these context information can be used in all context aware music recommendations. Finally, adopted experiments reveals that recommendations which apply these context information are acceptably similar to user’s selection in all circumstances.}
    }