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Breaking out of the box of recommendations: from items to packages

Breaking out of the box of recommendations: from items to packages,10.1145/1864708.1864739,Min Xie,Laks V. S. Lakshmanan,Peter T. Wood

Breaking out of the box of recommendations: from items to packages   (Citations: 1)
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Classical recommender systems provide users with a list of recommendations where each recommendation consists of a single item, e.g., a book or DVD. However, several applications can benefit from a system capable of recommending packages of items, in the form of sets. Sample applications include travel planning with a limited budget (price or time) and twitter users wanting to select worthwhile tweeters to follow given that they can deal with only a bounded number of tweets. In these contexts, there is a need for a system that can recommend top-k packages for the user to choose from. Motivated by these applications, we consider composite recommendations, where each recommendation comprises a set of items. Each item has both a value (rating) and a cost associated with it, and the user specifies a maximum total cost (budget) for any recommended set of items. Our composite recommender system has access to one or more component recommender system, focusing on different domains, as well as to information sources which can provide the cost associated with each item. Because the problem of generating the top recommendation (package) is NP-complete, we devise several approximation algorithms for generating top-k packages as recommendations. We analyze their efficiency as well as approximation quality. Finally, using two real and two synthetic data sets, we subject our algorithms to thorough experimentation and empirical analysis. Our findings attest to the efficiency and quality of our approximation algorithms for top-k packages compared to exact algorithms.
Conference: Conference on Recommender Systems - RecSys , pp. 151-158, 2010
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    • ...However, there are several applications that can benefit from a system capable of recommending packages of items [2]...
    • ...4A detailed comparison can be found in [2]...
    • ...For the composite set recommendation problem, we can adopt the algorithm template studied in our previous work [2], which is shown in Algorithm 1...
    • ...using MaxValBound [2] (line 6). The algorithm terminates if v(R o ) 1 V ; if not, it continues to access the next POI (lines 7‐8) 7 ...
    • ...Similar to [2], it can be shown that the proposed CR-Set-...
    • ...We have shown in previous work [2] that algorithms using the greedy heuristic often have performance very close to the instance optimal algorithm...
    • ...We have proven in our previous work [2] that for the top-k composite recommendation problem, if the algorithm for the optimal solution in Lawler’s procedure is replaced by an -approximation algorithm, instead of optimal top-k answers, we get an -approximation to the optimal set of top-k composite recommendations...

    Min Xieet al. CompRec-Trip: A composite recommendation system for travel planning

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