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4. Conclusion

We proposed BOR in this paper, an approach that extracts social requirements of SMA reviews and then
seeks matching requirements for each review. The combination of WordNet and word embedding has been
approved to achieve preferable results due to the enhancement of the word relatedness in classical WordNet-
based approaches. As we know, SMA developers receive huge numbers of reviews every day, making manual
analysis difficult and time-consuming. Thus, the application of BOR that filters irrelevant reviews helps in
cutting cost and speed up upgrading or improving the SMA. In addition, our proposed BOR also can be
expanded to different applications, as such sentiment analysis, system recommendation, application evaluation,
and so on.

Acknowledgments

This work is partially supported by MoHE under research code: FRGS/1/2020/ICT02/UKM/02/1

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