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Mining Users' Preference Similarities in E-commerce Systems Based on Webpage Navigation Logs

Ping Li, Chunxue Wu, Shaozhong Zhang, Xinwu Yu, Haidong Zhong
2017 International Journal of Computers Communications & Control  
Mining users' preference patterns in e-commerce systems is a fertile area for a great many application directions, such as shopping intention analysis, prediction and personalized recommendation.  ...  In this article, we propose a web browsing history mining based user preference discovery method for e-commerce systems.  ...  Personalized recommendation in e-commerce systems is deemed as one of the most popular applications that based on users' profile and preference extraction.  ... 
doi:10.15837/ijccc.2017.5.2565 fatcat:rxmunsqelvbk5jxn3gkjnnppeu

Clustering Approach to detect Profile Injection Attacks in Recommender System

Ashish Kumar, Deepak Garg, Prashant Singh
2017 International Journal of Computer Applications  
E-commerce recommender systems are vulnerable to the profile injection attacks, involving insertion of fake profiles into the system to influence the recommendations made to the users.  ...  The huge growth in the information and the count of visitors to the web sites especially on e-commerce in last few years creates some challenges for recommender systems.  ...  Among these two approaches of recommendation, for e-commerce recommender systems, collaborative filtering approach is most common.  ... 
doi:10.5120/ijca2017914031 fatcat:aryy4smqo5cd7ahocw3y7eun6q

Enterprise Online Product Recommendation Service Model based on Big Data Environment

W.W. Liu
2016 Chemical Engineering Transactions  
With the development and application of e-commerce, the research on enterprise online product recommendation service model under big data background has become a frontier issue.  ...  Collaborative filtering algorithm is improved based on domain ontology, which calculates semantic similarity of domain ontology from two angles of hierarchical similarity and attribute similarity.  ...  It has brought convenience and personalized service to users and huge economic benefits for e-commerce enterprise and has great significance to personalized information service for e-commerce.  ... 
doi:10.3303/cet1651128 doaj:09c0e859623d434e94c7e338e1333319 fatcat:wq5u3fpnajhk7mavy6skuoz67e

FHCC : A Soft Hierarchical Clustering Approach for Collaborative Filtering Recommendation

Kaiman Zeng, Nansong Wu, Xiaokun Yang, Lu Wang, Kang K. Yen
2016 International Journal of Data Mining & Knowledge Management Process  
Recommendation becomes a mainstream feature in nowadays e-commerce because of its significant contributions in promoting revenue and customer satisfaction.  ...  data for collaborative filtering recommendation.  ...  INTRODUCTION Recommendation service is gaining increasing attention in the big data era and has brought great benefit in e-commerce.  ... 
doi:10.5121/ijdkp.2016.6303 fatcat:byn2nvw53zfznd67ncckbyno3e

User Preference-oriented Collaborative Recommendation Algorithm in e-commerce

Huiying Gao, Susu Wang, Bofei Yang, Hangzhou Yang
2014 Journal of Software  
Aiming at the problem in an insufficient personalization of e-commerce recommendation system , a user preference-oriented network model is established in the paper.  ...  Collaborative recommendation is a key issue today in e-commerce, which helps users find the information of products which they are interested in from the mass of information.  ...  In the field of e-commerce recommendation, Kamak [11] proposed a fuzzy computing model of trust and credibility system, which has promoted the effect of recommendation system by the method of double  ... 
doi:10.4304/jsw.9.7.1886-1893 fatcat:6dxbivaqhvcxbgnu35gqakjl6a

Products Recommendation for Mobile Devices

Ruyther Parente da Costa, Caíque de Paula Pereira, Edna Dias Canedo
2017 Journal of Information Systems Engineering & Management  
The mobile application market and e-commerce sales have grown steadily, along with the growth of studies and product recommendation solutions implemented in e-commerce systems.  ...  Therefore, this work aims to customize a gift recommendation algorithm in the context of mobile devices using as main input the user preferences for the gifts recommendation in the Giftr application.  ...  And the following keywords in English were considered: • Algorithm; • Recommendation Algorithm; • Recommendation Algorithm based on profile; • E-commerce The search string created for the search was as  ... 
doi:10.20897/jisem.201716 fatcat:gtuytaodsjes7ow7nvhyviyvee

Conceptualize and Infer User Needs in E-commerce [article]

Xusheng Luo, Yonghua Yang, Kenny Q. Zhu, Yu Gong, Keping Yang
2019 arXiv   pre-print
Representing implicit user needs explicitly as nodes like "outdoor barbecue" or "keep warm for kids" in a knowledge graph, provides new imagination for various e- commerce applications.  ...  Without a proper definition of user needs in e-commerce, most industry solutions are not driven directly by user needs at current stage, which prevents them from further improving user satisfaction.  ...  Hierarchical categories and browse nodes 2 are ways of managing billions of items in e-commerce platforms and are usually used to represent user needs or interests [12, 37] .  ... 
arXiv:1910.03295v1 fatcat:lmc67ww6pjgkpamvshphu7kbb4

Acquiring the user's opinion by using a generalized Context-aware Recommender System for real-world applications

Chinta Venkata Murali Krishna, Dr G. Appa Rao
2018 International Journal of Engineering & Technology  
Here, we propose a generalized Context-aware recommender system that is suitable for all applications where a contextual segment plays a major role to find user's opinion in real-world applications.  ...  The same user may express or use completely different decision-making ways for various contexts to express the opinion .So, correct anticipation of user need depends upon the amount to which the relevant  ...  Conclusion Recommender Systems plays a major role in the e-commerce industry to find user's opinion.  ... 
doi:10.14419/ijet.v7i2.7.11087 fatcat:x3kddcsmvvc4xej7oc3duckb7e

Study of Recommendation System for Web Portals

Lokesh Sharma, Ashok Kumar Agrawal
2013 International Journal of Computer Applications  
Paper conclude with the applications of recommendation system and how they are increasing customer's to E-commerce. General Terms  ...  In this paper, introducing about Recommendation system and its various types with their corresponding technologies that are currently used in E-commerce web portals.  ...  COMPARISON IN VARIOUS RECOMMENDATION SYSTEMS Refer to Table 1 CONCLUSION Recommender System is a most advanced mass customization for web portals that increase E-commerce.  ... 
doi:10.5120/14601-2846 fatcat:m5l2j2spcvdytkh4l62tholffi

A framework for delivering personalized e-government services from a citizen-centric approach

Malak Al-hassan, Haiyan Lu, Jie Lu
2009 Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services - iiWAS '09  
The Pe-Gov framework has the potential to outperform the existing e-Gov service systems as illustrated by two real life examples  ...  This paper proposes a new conceptual framework for delivering personalized e-government services to citizens from a citizen-centric approach, called Pe-Gov service framework.  ...  User Profile DB User profiling would help e-Gov service systems to communicate effectively and efficiently with their users.  ... 
doi:10.1145/1806338.1806419 dblp:conf/iiwas/Al-hassanLL09 fatcat:p3a5yplk3rhhvfbz7jcv2x75ue

A Survey of Deep Learning Approaches for Recommendation Systems

Jun Yi Liu
2018 Journal of Physics, Conference Series  
Due to the explosive information, recommendation system has been an important part of people's life. It can suggest or predict information based on the user's preference to help user save time.  ...  This paper provides a survey of recommendation systems, which focuses on deep learning approaches and the system of applications.  ...  Wu et al. introduced a real-time recommendation service for e-commerce system through exploit current viewing history of the user.  ... 
doi:10.1088/1742-6596/1087/6/062022 fatcat:2mep7pcyvrdvldwq7z3ts6w6gm

Mobile Gift Recommendation Algorithm

Caíque de Paula Pereira, Ruyther Parente da Costa, Edna Dias Canedo
2017 Proceedings of the 19th International Conference on Enterprise Information Systems  
The mobile application market and e-commerce sales have grown steadily, along with the growth of studies and product recommendation solutions implemented in e-commerce systems.  ...  Therefore, this work aims to customize a gift recommendation algorithm in the context of mobile devices using as main input the user preferences for the gifts recommendation in the Giftr application.  ...  d j occur based on the same e-commerce system.  ... 
doi:10.5220/0006330405650573 dblp:conf/iceis/PereiraCC17 fatcat:ckfmaqalzfeb3a3gomho5o3yhm

An Accuracy Improvement of Detection of Profile-Injection Attacks in Recommender Systems using Outlier Analysis

Jiten H.Dhimmar, Raksha Chauhan
2015 International Journal of Computer Applications  
E-Commerce recommender systems are affected by various kinds of profile-injection attacks where several fake user profiles are entered into the system to influence the recommendations made to the users  ...  Experiments show that an accuracy of ECLARANS algorithm for detection of profile-injection attack for E-commerce recommender system is more than PAM clustering algorithm.  ...  Experiment results of proposed method show that ECLARANS algorithm improves the accuracy of detection of profile-injection attack compare to PAM clustering algorithm for E-commerce recommender system.  ... 
doi:10.5120/21737-4930 fatcat:otjfgo6mf5gyld7ryrrfxfo4oa

Time-weighted Attentional Session-Aware Recommender System [article]

Mei Wang, Weizhi Li, Yan Yan
2019 arXiv   pre-print
And then, our ASARS framework promotes two novel models: (1) an inter-session temporal dynamic model that captures the long-term user interaction for RNN recommender system.  ...  Our extensive experiments on four real datasets from different domains demonstrate the effectiveness and large improvement of ASARS for personalized recommendation.  ...  Example In an e-commerce recommender system, a user Alice may come with a certain intent for some kitchen hand soap that she wants to buy at present.  ... 
arXiv:1909.05414v1 fatcat:wprgje6jsbh33a4djewf3r5qda

Attacking Black-box Recommendations via Copying Cross-domain User Profiles [article]

Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li
2020 arXiv   pre-print
Recently, recommender systems that aim to suggest personalized lists of items for users to interact with online have drawn a lot of attention.  ...  Recent studies have shown that these deep learning models (in particular for recommendation systems) are vulnerable to attacks, such as data poisoning, which generates users to promote a selected set of  ...  For example, movie recommendation platforms IMDb and Netflix share a lot of movies and e-commerce sites Amazon and eBay have millions of products in common.  ... 
arXiv:2005.08147v1 fatcat:drtu7fig3nawrowmwjbnjlapua
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