?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Learning+to+Advertise+for+Organic+Traffic+Maximization+in+E-Commerce+Product+Feeds&rft.creator=Chen%2C+D&rft.creator=Jin%2C+J&rft.creator=Zhang%2C+W&rft.creator=Pan%2C+F&rft.creator=Niu%2C+L&rft.creator=Yu%2C+C&rft.creator=Wang%2C+J&rft.creator=Li%2C+H&rft.creator=Xu%2C+J&rft.creator=Gai%2C+K&rft.description=Most+e-commerce+product+feeds+provide+blended+results+of+advertised+products+and+recommended+products+to+consumers.+The+underlying+advertising+and+recommendation+platforms+share+similar+if+not+exactly+the+same+set+of+candidate+products.+Consumers'+behaviors+on+the+advertised+results+constitute+part+of+the+recommendation+model's+training+data+and+therefore+can+influence+the+recommended+results.+We+refer+to+this+process+as+Leverage.+Considering+this+mechanism%2C+we+propose+a+novel+perspective+that+advertisers+can+strategically+bid+through+the+advertising+platform+to+optimize+their+recommended+organic+traffic.+By+analyzing+the+real-world+data%2C+we+first+explain+the+principles+of+Leverage+mechanism%2C+i.e.%2C+the+dynamic+models+of+Leverage.+Then+we+introduce+a+novel+Leverage+optimization+problem+and+formulate+it+with+a+Markov+Decision+Process.+To+deal+with+the+sample+complexity+challenge+in+model-free+reinforcement+learning%2C+we+propose+a+novel+Hybrid+Training+Leverage+Bidding+(HTLB)+algorithm+which+combines+the+real-world+samples+and+the+emulator-generated+samples+to+boost+the+learning+speed+and+stability.+Our+offline+experiments+as+well+as+the+results+from+the+online+deployment+demonstrate+the+superior+performance+of+our+approach.&rft.publisher=Association+for+Computing+Machinery+(ACM)&rft.contributor=Zhu%2C+W&rft.contributor=Tao%2C+D&rft.contributor=Cheng%2C+X&rft.contributor=Cui%2C+P&rft.contributor=Rundensteiner%2C+E&rft.contributor=Carmel%2C+D&rft.contributor=He%2C+Q&rft.contributor=Yu%2C+JX&rft.date=2019-11-03&rft.type=Proceedings+paper&rft.publisher=28th+ACM+International+Conference+on+Information+and+Knowledge+Management+(CIKM)&rft.language=eng&rft.source=+++++In%3A+Zhu%2C+W+and+Tao%2C+D+and+Cheng%2C+X+and+Cui%2C+P+and+Rundensteiner%2C+E+and+Carmel%2C+D+and+He%2C+Q+and+Yu%2C+JX%2C+(eds.)+CIKM+'19%3A+Proceedings+of+the+28th+ACM+International+Conference+on+Information+and+Knowledge+Management.++(pp.+pp.+2527-2535).++Association+for+Computing+Machinery+(ACM)%3A+New+York%2C+NY%2C+USA.+(2019)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10116271%2F1%2F1908.06698.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10116271%2F&rft.rights=open