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Synergy between Customer Segmentation and personalization

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Journal of Systems Science and Systems Engineering 2021年第3期30卷 276-287页

作者： Jingtong Zhao Department of Industrial Engineering Operations Research Columbia UniversityNew YorkNY10027U.S.

Personalized pricing is on the rise in the retail industry,and it’s been used in many service *** pricing assumes that the platform has an idea of who the customer is,and allows the platform to incentivize the customers based on their characteristics and *** this work,we consider a personalized pricing problem with revisiting *** assume a customer’s utility depends on some feature information and some unobserved personal *** the case where customer utilities are unknown,we propose a heuristic that combines the idea of binary search and feature-based pricing,and show that it outperforms common *** also demonstrate that if we have some information about either the customer utility or the dependence on the feature information,then we can learn the other much faster,and this is what we mean by the synergy between customer segmentation and *** observation can help managers make better personalized decisions for customers that repeatedly interact with the platform.

关键词： Pricing algorithms heuristics personalization

Evolutionary Game Analysis on E-Commerce personalization and Privacy Protection

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Wuhan University Journal of Natural Sciences 2018年第1期23卷 17-24页

作者： LI Yanhui XU Lu LIU Bailing School of Information Management Central China Normal University

Personalized products and services in e-commerce bring consumers many new experiences, but also trigger a series of information security issues. Considering the bounded rationality of the game participants, in this paper, we propose an evolutionary game model of privacy protection between firms and consumers based on e-commerce personalization. Evolutionary stable strategies（ESSs） are obtained from the equilibrium points according to the model analysis, and then simulation experiments are launched to validate the decision-making results and the influencing mechanism of various factors. The results show that the model can eventually evolve toward a win-win situation by wisely varying its various factors, such as ratios of initial strategies, cost of privacy protection, commodity prices, and other related factors. Further, we find that reducing the possibility of the privacy breach under the premise of privacy protection can help promote the e-commerce personalization.

关键词： e-commerce personalization privacy protection evolutionary game

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Prototypicality Gradient and Similarity Measure: A Semiotic-Based Approach Dedicated to Ontology personalization

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Intelligent Information Management 2010年第2期2卷 65-79页

作者： X. Aime F. Furst P. Kuntz F. Trichet 不详

This paper introduces a new approach dedicated to the Ontology personalization. Inspired by works in Cognitive Psychology, our work is based on a process which aims at capturing the user-sensitive relevance of the categorization process, that is the one which is really perceived by the end-user. Practically, this process consists in decorating the Specialization/Generalization links (i.e. the is-a links) of the hierarchy of concepts with 2 gradients. The goal of the first gradient, called Conceptual Prototypicality Gradient, is to capture the user-sensitive relevance of the categorization process, that is the one which is perceived by the end-user. As this gradient is defined according to the three aspects of the semiotic triangle (i.e. intentional, extensional and expressional dimension), we call it Semiotic based Prototypicality Gradient. The objective of the second gradient, called Lexical Prototypicality Gradient, is to capture the user-sensitive relevance of the lexicalization process, i.e. the definition of a set of terms used to denote a concept. These gradients enrich the initial formal semantics of an ontology by adding a pragmatics defined according to a context of use which depends on parameters like culture, educational background and/or emotional context of the end-user. This paper also introduces a new similarity measure also defined in the context of a semiotic-based approach. The first originality of this measure, called SEMIOSEM, is to consider the three semiotic dimensions of the conceptualization underlying an ontology. Thus, SEMIOSEM aims at aggregating and improving existing extensional-based and intentional-based measures. The second originality of this measure is to be context-sensitive, and in particular user-sensitive. This makes SEMIOSEM more flexible, more robust and more close to the end-user’s judgment than the other similarity measures which are usually only based on one aspect of a conceptualization and never take the end-user’s percep

关键词： Semantic Measure Conceptual Prototypicality Lexical Prototypicality Gradient Ontology personalization Semiotics

Beyond Algorithms: A Comprehensive Analysis of AI-Driven personalization in Strategic Communications

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Journal of Computer and Communications 2024年第10期12卷 112-131页

作者： Natalie Nkembuh Department of Communication European International University Paris France

This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.

关键词： Artificial Intelligence (AI) Strategic Communications personalization Machine Learning Natural Language Processing (NLP) Customer Engagement Data Analytics Digital Marketing Audience Segmentation Communication Effectiveness AI Ethics Conversion Optimization Predictive Analytics Content personalization Marketing Automation

Personalized Privacy-Preserving Trajectory Data Publishing

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Chinese Journal of Electronics 2017年第2期26卷 285-291页

作者： LU Qiwei WANG Caimei XIONG Yan XIA Huihua HUANG Wenchao GONG Xudong School of Computer Science and Technology University of Science and Technology of China Department of Computer Science and Engineering Hefei University

Due to the popularity of mobile internet and location-aware devices,there is an explosion of location and tra jectory data of moving objects.A few proposals have been proposed for privacy preserving tra jectory data publishing,and most of them assume the attacks with the same adversarial background *** practice,different users have different privacy *** non-personalized privacy assumption does not meet the personalized privacy requirements,meanwhile,it looses the chance to achieve better utility by taking advantage of differences of users’ privacy *** study the personalized tra jectory k-anonymity criterion for trajectory data ***,we explore and propose an overall framework which provides privacy preserving services based on users’ personal privacy requests,including tra jectory clustering,editing and *** demonstrate the efficiency and effectiveness of our scheme through experiments on real world dataset.

关键词： personalization Tra jectory data Privacy-preserving data publishing

Personalized News Recommendation:A Review and an Experimental Investigation

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Journal of Computer Science & Technology 2011年第5期26卷 754-766页

作者：李磊王丁丁朱顺痣李涛 School of Computing and Information Sciences Florida International University Department of Computer Science and Technology Xiamen University of Technology

Online news articles,as a new format of press releases,have sprung up on the *** its convenience and recency,more and more people prefer to read news online instead of reading the paper-format press ***,a gigantic amount of news events might be released at a rate of hundreds,even thousands per hour.A challenging problem is how to efficiently select specific news articles from a large corpus of newly-published press releases to recommend to individual readers,where the selected news items should match the reader＇s reading preference as much as *** issue refers to personalized news ***,personalized news recommendation has become a promising research direction as the Internet provides fast access to real-time information from multiple sources around the *** personalized news recommendation systems strive to adapt their services to individual users by virtue of both user and news content information.A variety of techniques have been proposed to tackle personalized news recommendation,including content-based,collaborative filtering systems and hybrid versions of these *** this paper,we provide a comprehensive investigation of existing personalized news *** discuss several essential issues underlying the problem of personalized news recommendation,and explore possible solutions for performance ***,we provide an empirical study on a collection of news articles obtained from various news websites,and evaluate the effect of different factors for personalized news *** hope our discussion and exploration would provide insights for researchers who are interested in personalized news recommendation.

关键词： news recommendation personalization scalability user profiling modeling ranking

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Personalized gesture interactions for cyber-physical smart-home environments

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Science China(Information Sciences) 2017年第7期60卷 144-158页

作者： Yihua LOU Wenjun WU Radu-Daniel VATAVU Wei-Tek TSAI State Key Laboratory of Software Development Environment Beihang University Mint Viz Research Lab Integrated Center for Research Developmentand Innovation in Advanced MaterialsNanotechnologies and Distributed Systems for Fabrication and Control (MANSiD) & Department of Computer Science University Stefan cel Mare of Suceava

A gesture-based interaction system for smart homes is a part of a complex cyber-physical environment, for which researchers and developers need to address major challenges in providing personalized gesture interactions. However, current research efforts have not tackled the problem of personalized gesture recognition that often involves user identification. To address this problem, we propose in this work a new event-driven service-oriented framework called gesture services for cyber-physical environments(GS-CPE) that extends the architecture of our previous work gesture profile for web services(GPWS). To provide user identification functionality, GS-CPE introduces a two-phase cascading gesture password recognition algorithm for gesture-based user identification using a two-phase cascading classifier with the hidden Markov model and the Golden Section Search, which achieves an accuracy rate of 96.2% with a small training dataset. To support personalized gesture interaction, an enhanced version of the Dynamic Time Warping algorithm with multiple gestural input sources and dynamic template adaptation support is implemented. Our experimental results demonstrate the performance of the algorithm can achieve an average accuracy rate of 98.5% in practical scenarios. Comparison results reveal that GS-CPE has faster response time and higher accuracy rate than other gesture interaction systems designed for smart-home environments.

关键词： gesture interaction personalization gesture recognition user identification event-driven architec ture

A Survey of Multimodal Controllable Diffusion Models

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Journal of Computer Science & Technology 2024年第3期39卷 509-541页

作者：江锐郑光聪李藤杨天瑞王井东李玺 College of Computer Science and Technology Zhejiang UniversityHangzhou310007China Department of Mathematics Nanjing UniversityNanjing 210023China Baidu Visual Technology Department Baidu Inc.Beijing 100085China IEEE

Diffusion models have recently emerged as powerful generative models,producing high-fidelity samples across *** this,they have two key challenges,including improving the time-consuming iterative generation process and controlling and steering the generation *** surveys provide broad overviews of diffusion model ***,they lack comprehensive coverage specifically centered on techniques for controllable *** survey seeks to address this gap by providing a comprehensive and coherent review on controllable generation in diffusion *** provide a detailed taxonomy defining controlled generation for diffusion *** generation is categorized based on the formulation,methodologies,and evaluation *** enumerating the range of methods researchers have developed for enhanced control,we aim to establish controllable diffusion generation as a distinct subfield warranting dedicated *** this survey,we contextualize recent results,provide the dedicated treatment of controllable diffusion model generation,and outline limitations and future *** demonstrate applicability,we highlight controllable diffusion techniques for major computer vision tasks *** consolidating methods and applications for controllable diffusion models,we hope to catalyze further innovations in reliable and scalable controllable generation.

关键词： diffusion model controllable generation application personalization

Personalized query suggestion diversification in information retrieval

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Frontiers of Computer Science 2020年第3期14卷 129-141页

作者： Wanyu CHEN Fei CAI Honghui CHEN Maarten DE RIJKE Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410073China Informatics Institute University of AmsterdamAmsterdam1098XHThe Netherlands

Query suggestions help users refine their queries after they input an initial *** work on query suggestion has mainly concentrated on approaches that are similarity-based or context-based,developing models that either focus on adapting to a specific user(personalization)or on diversifying query aspects in order to maximize the probability of the user being satisfied(diversification).We consider the task of generating query suggestions that are both personalized and *** propose a personalized query suggestion diversification(PQSD)model,where a user's long-term search behavior is injected into a basic greedy query suggestion diversification model that considers a user's search context in their current *** aspects are identified through clicked documents based on the open directory project(ODP)with a latent dirichlet allocation(LDA)topic *** quantify the improvement of our proposed PQSD model against a state-of-the-art baseline using the public america online(AOL)query log and show that it beats the baseline in terms of metrics used in query suggestion ranking and *** experimental results show that PQSD achieves its best performance when only queries with clicked documents are taken as search context rather than all queries,especially when more query suggestions are returned in the list.

关键词： query suggestion personalization query suggestion diversification