Abstract
In the contemporary era, online reviews have an impact on people of all walks of life while choosing appropriate reviews that satisfied user preferences. Personalized reviews selection that is highly relevant to high coverage concerning matching with micro-reviews is the main problem that is considered in this paper. Toward this end, select a personalized subset of reviews are suggested. However, none of the existing research has taken into consideration the personalization of reviews. We proposed a framework known as PeRView for personalized review selection using micro-reviews. The proposed approach shows that our framework can determine and select the best subset of personalized reviews. Based on metric evaluation approach which considered personalized matching score and subset size.
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Acknowledgement
This work is supported by the practical training project of high-level talents cross-training of Beijing colleges and universities (BUCEA-2018).
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Al-khiza’ay, M., Alallaq, N., Alanoz, Q., Al-Azzawi, A., Maheswari, N. (2018). Personalize Review Selection Using PeRView. In: Liu, W., Giunchiglia, F., Yang, B. (eds) Knowledge Science, Engineering and Management. KSEM 2018. Lecture Notes in Computer Science(), vol 11061. Springer, Cham. https://doi.org/10.1007/978-3-319-99365-2_21
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DOI: https://doi.org/10.1007/978-3-319-99365-2_21
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