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Furthermore, we find that there is a substitute relationship between user recommendation volume and system recommendation strength.
Using data on the digital camera category from the largest business-to-consumer platform in China, Tmall.com, we use linear panel data models to examine the impact of user recommendation volume and valence, and system recommendation strength on product sales, controlling for relevant factors at the recommended product, product recommender, product category, and time unit levels.
Fig. 16 User recommendation on social network.
The first pool approaches produce individual user recommendation based on graph models [16, 17].
For future work, we plan to use our insights to design personalized user recommendation algorithms.
It shows that the prediction performance of the small-scale user recommendation system is mainly dependent on the multi-objective partitioning, and the multi-objective coordination performance is mainly reflected in the large-scale user recommendation system.
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Don't online services have user recommendations, too?
Already, a number of mechanisms have emerged, based around user recommendations.
Google's local effort does not revolve around news, but rather business listings and user recommendations.
Overall, user recommendations are more effective than system recommendations in driving product sales.
The project will increase social media conversations, build an extended audience on Twitter and Facebook and drive user recommendations on the campaign's interactive map.
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