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Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application [article]

Yujing Hu, Qing Da, Anxiang Zeng, Yang Yu, Yinghui Xu
2018 arXiv   pre-print
In e-commerce platforms such as Amazon and TaoBao, ranking items in a search session is a typical multi-step decision-making problem.  ...  Experiments are conducted in simulation and TaoBao search engine.  ...  ACKNOWLEDGMENTS We would like to thank our colleague âĹŠ Yusen Zhan for useful discussions and supports of this work.  ... 
arXiv:1803.00710v3 fatcat:mvf3tuhkprfhpcz6ojgousfqk4

Accelerating E-Commerce Search Engine Ranking by Contextual Factor Selection [article]

Yusen Zhan, Qing Da, Fei Xiao, An-xiang Zeng, Yang Yu
2018 arXiv   pre-print
We inject CFS into the search engine ranking score to accelerate the engine, considering both ranking effectiveness and efficiency.  ...  Solving the problem by reinforcement learning, we propose the RankCFS, which has been assessed in an off-line environment as well as a real-world on-line environment (Taobao.com).  ...  achieves both of effectiveness and efficiency in terms of e-commerce search engine.  ... 
arXiv:1803.00693v3 fatcat:glsnmphounfz3ozksd23g6dcq4

Comparison Shopping Engines

Ghizlane LAGHMARI, Sanae KHALI, M'hamed AIT
2019 International Journal of Advanced Computer Science and Applications  
As a result, he displays a confused and suspicious attitude and desperately turns to the comparison shopping engines (CSEs) to save time and identify the best matching offer for his search request.  ...  Thus, the article in question serves as an investigation of the comparison shopping engines to know if they are up to the task of satisfying the needs of the e-consumer.  ...  In her work, Soe Tyrant used the interactive power of the Web to analyze user behavior to capture dynamic consumer preferences over time, whereas for ranking, she used learning by reinforcing time differences  ... 
doi:10.14569/ijacsa.2019.0100771 fatcat:tm3eramxr5csnkvhm4tdh4si2a

A Bird's Eye View on Requirements Engineering and Machine Learning

Tahira Iqbal, Parisa Elahidoost, Levi Lucio
2018 2018 25th Asia-Pacific Software Engineering Conference (APSEC)  
Machine learning (ML) has demonstrated practical impact in a variety of application domains. Software engineering is a fertile domain where ML is helping in automating different tasks.  ...  We found that the impact of ML can be observed in requirement elicitation, analysis and specification, validation and management.  ...  In reinforcement learning, an agent has to find a sequence of actions leading to a success.  ... 
doi:10.1109/apsec.2018.00015 dblp:conf/apsec/IqbalEL18 fatcat:mfqly5jrafeohilv2eks2t2tda

New Assistance Site for Recommendation using Collaborative Filtering and Authenticate User using Face Detection

Ahmad Abulharish Jamil
2020 International Journal for Research in Applied Science and Engineering Technology  
The previous recommendation systems model users' evolving, numerous and multi-aspect preferences to get recommendations in numerous domains/applications, about to improve the citizens' everyday life by  ...  For authenticating the user's exploitation face detection techniques. and eventually, apply 2 varieties of product search are text and voice.  ...  for product search and recommendation in e-commerce.  ... 
doi:10.22214/ijraset.2020.6114 fatcat:wfn5fog4zva3tmn7janocirxxu

A community-aware search engine

Rodrigo B. Almeida, Virgilio A. F. Almeida
2004 Proceedings of the 13th conference on World Wide Web - WWW '04  
In this paper, we describe a novel ranking technique for personalized search services that combines content-based and community-based evidences.  ...  Current search technologies work in "one size fits all" fashion. Therefore, the answer to a query is independent of specific user information need.  ...  The authors would like to thank the anonymous service owners and operators for enabling this research to proceed by providing us access to their logs.  ... 
doi:10.1145/988672.988728 dblp:conf/www/AlmeidaA04 fatcat:yglytstaareq3d3nqgofbond6e

Search Engines that Learn from Their Users

Anne Schuth
2016 SIGIR Forum  
Our product search site was a commercial e-commerce website, REGIO. Our web search site a commercial web search engine, Seznam.  ...  We have so far conducted experiments with two specific sites for ad-hoc search: product search on an e-commerce site and web search on large scale web search engine.  ...  Historical click and usage data is available in meaningful quantities. 4 . Most importantly, because we use head queries, participants' systems do not need to respond in real-time to user queries (cf  ... 
doi:10.1145/2964797.2964817 fatcat:lk24shg7dzbyzk7kkr4x6cjbna

AEFE: Automatic Embedded Feature Engineering for Categorical Features [article]

Zhenyuan Zhong, Jie Yang, Yacong Ma, Shoubin Dong, Jinlong Hu
2021 arXiv   pre-print
The challenge of solving data mining problems in e-commerce applications such as recommendation system (RS) and click-through rate (CTR) prediction is how to make inferences by constructing combinatorial  ...  Experiments conducted on some typical e-commerce datasets indicate that our method outperforms the classical machine learning models and state-of-the-art deep learning models.  ...  feature construction, in e-commerce applications, and keeps good interpretability.  ... 
arXiv:2110.09770v1 fatcat:rhiaopkft5hm3gulxfgwjdluqe

Conversational Agents in Software Engineering: Survey, Taxonomy and Challenges [article]

Quim Motger, Xavier Franch, Jordi Marco
2021 arXiv   pre-print
The latest contributions in the field, including deep learning approaches like recurrent neural networks, the potential of context-aware strategies and user-centred design approaches, have brought back  ...  As a result, this research proposes a holistic taxonomy of the different dimensions involved in the conversational agents' field, which is expected to help researchers and to lay the groundwork for future  ...  Education conversational agents can be found as e-learning tools for student assistance in the learning process [124] and as automated tutoring agents [120] .  ... 
arXiv:2106.10901v1 fatcat:bqs3tfkjcjhmblnd6lcysttlgy

Combining Website Search Engine Optimization with Advanced Web Log Analysis

Seamus Dromey, Ciara Heavin, Karen Neville
2005 European Conference on Information Systems  
The system (Googalyser) utilizes Web logs and content analysis to provide decisive information to Web developers in order to improve the cases ranking through for example www. Google.com.  ...  The system described illustrates the complexity of the competition between organizations to be highly ranked by leading search engines.  ...  a Web pages Google Search engine ranking and the traffic received to a Web page.  ... 
dblp:conf/ecis/DromeyHN05 fatcat:fzgawgoqjzbb7fmowykfen5opi

A Reinforcement Learning Based Model for Adaptive Service Quality Management in E-Commerce Websites

Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani
2019 Business & Information Systems Engineering  
This paper proposes a reinforcement-learning based adaptive e-commerce system model that adapts the service quality level for different Web sessions within the customer's navigation in order to maximize  ...  The learner agent noted as e-commerce supply chain manager (ECSCM) agent allocates a service quality level to the customer's request based on his/her navigation pattern in the e-commerce Website and selects  ...  Improving e-commerce system's performance Our work QoS adaptation Reinforcement learning Profit maximization Search provider E-mail provider E-payment provider Storage service provider  ... 
doi:10.1007/s12599-019-00583-6 fatcat:363ud4qk4remja3jhdpqsae3re

Interpretable Attribute-based Action-aware Bandits for Within-Session Personalization in E-commerce

Xu Liu, Congzhe Su, Amey Barapatre, Xiaoting Zhao, Diane Hu, Chu-Cheng Hsieh, Jingrui He
2021 IEEE Data Engineering Bulletin  
We train and evaluate OPAR on a real-world e-commerce search ranking system and benchmark it against 4 state-of-the-art baselines on 8 datasets and show an improvement in ranking performance across all  ...  As such, it is increasingly important for e-commerce ranking systems to quickly learn a buyer's fine-grained preferences and re-rank items based on their most recent activity within the session.  ...  Hu et al. in [13] proposed to use reinforcement learning to learn an optimal ranking policy that maximizes the expected accumulative rewards in a search session.  ... 
dblp:journals/debu/0016SBZHHH21 fatcat:z3zlis547fe6nf3kxsyv6vfwpe

Recommender systems in model-driven engineering

Lissette Almonte, Esther Guerra, Iván Cantador, Juan de Lara
2021 Journal of Software and Systems Modeling  
AbstractRecommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms.  ...  This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods  ...  of Science (projects MASSIVE, RTI2018-095255-B-I00, and FIT, PID2019-108965GB-I00) and by the R&D programme of Madrid (Project FORTE, P2018/TCS-4314).  ... 
doi:10.1007/s10270-021-00905-x fatcat:x5ju2ye5ozbtflrzknohy2yfeu

Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities [article]

Zhaoyi Xu, Joseph Homer Saleh
2020 arXiv   pre-print
Overall, we argue that ML is capable of providing novel insights and opportunities to solve important challenges in reliability and safety applications.  ...  We then look back and review the use of ML in reliability and safety applications.  ...  Clustering methods are widely used in a host of applications, from image segmentation and object recognition, to document retrieval/data mining, genomics, and countless e-commerce applications.  ... 
arXiv:2008.08221v1 fatcat:qhbkiepabfaz7afhctqutncheq

Value-based software engineering

Barry Boehm
2003 Software engineering notes  
and practiced as largely logical activities; and a "separation of concerns" is practiced, in which the responsibility of software engineers is confined to turning software requirements into verified code  ...  reinforce each other.  ...  The definition of "engineering" in [36] is "the application of science and mathematics by which the properties of matter and sources of energy in nature are made useful to people."  ... 
doi:10.1145/638750.638775 fatcat:h7t3vdne6bgepnrb7rwn5lpl2q
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