Whole-Chain Recommendations

With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in developing RL-based recommender systems. In practical recommendation sessions, users will sequentially access multiple scenarios, such as the entrance pages and the item detail pages, and each scenario has its specific characteristics. However, the majority of existing RL-based recommender systems focus on optimizing one strategy for all scenarios or separately optimizing each strategy, which could lead to sub-optimal overall performance. In this paper, we study the recommendation problem with multiple (consecutive) scenarios, i.e., whole-chain recommendations. We propose a multi-agent RL-based approach (DeepChain), which can capture the sequential correlation among different scenarios and jointly optimize multiple recommendation strategies. To be specific, all recommender agents (RAs) share the same memory of users' historical behaviors, and they work collaboratively to maximize the overall reward of a session. Note that optimizing multiple recommendation strategies jointly faces two challenges in the existing model-free RL model - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced. In this paper, we introduce model-based RL techniques to reduce the training data requirement and execute more accurate strategy updates. The experimental results based on a real e-commerce platform demonstrate the effectiveness of the proposed framework.Comment: 29th ACM International Conference on Information and Knowledge Managemen

1943 Fertilizer Recommendations

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Management recommendations

The acute succession problem justifies an opportunistic use of all suitable methods on the short-term (10 years). The ban on winter burning should be (temporally) lifted. The mown area should be enlarged by activating volunteers, raising budgets and funds for mowing of BNP-owned peatlands and by using peat harvesters. BNP and farmers should co-operate to raise funds and conclude Management Agreements for livestock farming on private and BNP-owned peatland. Agreements should include the use of Biebrza hay and litter. In the longer term (>10 years) extensive grazing seems the most promising tool. It may be implemented as traditional dairy farming, ranching of beef cattle, horses or (semi-) wild herbivores or as Wilderness. Suitability and feasibility may differ between the three basins. The entry of Poland to the EU will affect the feasibility of the strategie

Making recommendations bandwidth aware

This paper asks how much we can gain in terms of bandwidth and user satisfaction, if recommender systems became bandwidth aware and took into account not only the user preferences, but also the fact that they may need to serve these users under bandwidth constraints, as is the case over wireless networks. We formulate this as a new problem in the context of index coding: we relax the index coding requirements to capture scenarios where each client has preferences associated with messages. The client is satisfied to receive any message she does not already have, with a satisfaction proportional to her preference for that message. We consistently find, over a number of scenarios we sample, that although the optimization problems are in general NP-hard, significant bandwidth savings are possible even when restricted to polynomial time algorithms

Dairy feeding recommendations / 1060

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Future challenges and recommendations

Rapid advances in information technology and telecommunications, and in particular mobile and wireless communications, converge towards the emergence of a new type of “infostructure” that has the potential of supporting a large spectrum of advanced services for healthcare and health. Currently the ICT community produces a great effort to drill down from the vision and the promises of wireless and mobile technologies and provide practical application solutions. Research and development include data gathering and omni-directional transfer of vital information, integration of human machine interface technology into handheld devices and personal applications, security and interoperability of date and integration with hospital legacy systems and electronic patient record. The ongoing evolution of wireless technology and mobile device capabilities is changing the way healthcare providers interact with information technologies. The growth and acceptance of mobile information technology at the point of care, coupled with the promise and convenience of data on demand, creates opportunities for enhanced patient care and safety. The developments presented in this section demonstrate clearly the innovation aspects and trends towards user oriented applications