Abstract
Nowadays, Recommender System is quite a useful system which helps people to navigate through complex items. There are many different recommender systems proposed and many business solutions have been found. But, because of the high complexity and uncertainty of the problem there is no best approach found. Recent research in the stream not just limited to the accuracy of the system. There are many another factors such as serendipity means as surprise, is defined as the finding the unexpected as well as useful items for the user. In our system, we are providing serendipity by the intrinsic accidents and user will find the value by applying their knowledge on it which says sagacity. We considered this mechanism as serendipity-oriented recommender system. Our idea is to give serendipity-oriented recommender system by Item Amalgamation Approach. The core logic of this technique is to find the items which have common features of the given input items by the user. We are considering benchmark and well known dataset MovieLens dataset for our Approach.
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Shah, R., Patel, A., Amin, K. (2016). Item Amalgamation Approach for Serendipity-Oriented Recommender System. In: Satapathy, S., Joshi, A., Modi, N., Pathak, N. (eds) Proceedings of International Conference on ICT for Sustainable Development. Advances in Intelligent Systems and Computing, vol 409. Springer, Singapore. https://doi.org/10.1007/978-981-10-0135-2_39
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DOI: https://doi.org/10.1007/978-981-10-0135-2_39
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