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Personalization Techniques and Recommender Systems最新文献

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An Experimental Study of Feature Selection Methods for Text Classification 文本分类特征选择方法的实验研究
Personalization Techniques and Recommender Systems Pub Date : 2008-04-01 DOI: 10.1142/9789812797025_0012
Gulden Uchyigit, K. Clark
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引用次数: 3
Personalization Techniques and Recommender Systems 个性化技术和推荐系统
Personalization Techniques and Recommender Systems Pub Date : 2008-04-01 DOI: 10.1142/6788
Gulden Uchyigit, Matthew Y. Ma
{"title":"Personalization Techniques and Recommender Systems","authors":"Gulden Uchyigit, Matthew Y. Ma","doi":"10.1142/6788","DOIUrl":"https://doi.org/10.1142/6788","url":null,"abstract":"The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed. \u0000 \u0000The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems. \u0000 \u0000This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems.","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122243081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 32
Identifying and Analyzing User Model Information from Collaborative Filtering Datasets 从协同过滤数据集中识别和分析用户模型信息
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0007
J. Griffith, C. O'Riordan, H. Sorensen
{"title":"Identifying and Analyzing User Model Information from Collaborative Filtering Datasets","authors":"J. Griffith, C. O'Riordan, H. Sorensen","doi":"10.1142/9789812797025_0007","DOIUrl":"https://doi.org/10.1142/9789812797025_0007","url":null,"abstract":"","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115381917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Personalization Strategies and Semantic Reasoning: Working in tandem in Advanced Recommender Systems 个性化策略和语义推理:在高级推荐系统中协同工作
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0008
Y. Blanco-Fernández, J. Pazos-Arias, A. Gil-Solla, M. Cabrer, Martín López Nores
{"title":"Personalization Strategies and Semantic Reasoning: Working in tandem in Advanced Recommender Systems","authors":"Y. Blanco-Fernández, J. Pazos-Arias, A. Gil-Solla, M. Cabrer, Martín López Nores","doi":"10.1142/9789812797025_0008","DOIUrl":"https://doi.org/10.1142/9789812797025_0008","url":null,"abstract":"","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"11 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129748951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Personalization-Privacy Tradeoffs in Adaptive Information Access 自适应信息访问中的个性化-隐私权衡
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0001
Barry Smyth
{"title":"Personalization-Privacy Tradeoffs in Adaptive Information Access","authors":"Barry Smyth","doi":"10.1142/9789812797025_0001","DOIUrl":"https://doi.org/10.1142/9789812797025_0001","url":null,"abstract":"As online information continues to grow at an exponential rate our ability to access this information effectively does not, and users are often frustrated by how difficult it is to locate the right information quickly and easily. So-called personalization technology is a potential solution to this information overload problem: by automatically learning about the needs and preferences of users, personalized information access solutions have the potential to offer users a more proactive and intelligent form of information access that is sensitive to their long-term preferences and current needs. In this paper, we document two case-studies of the use of personalization techniques to support information browsing and search. In addition, we consider the inevitable privacy issues that go hand-in-hand with profiling and personalization techniques and highlight the importance of striking the right balance between privacy and personalization when it comes to the development and deployment of practical systems.","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121320375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
User Modelling Sharing for Adaptive e-Learning and Intelligent Help 自适应电子学习和智能帮助的用户建模共享
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0004
K. Kabassi, M. Virvou, G. Tsihrintzis
{"title":"User Modelling Sharing for Adaptive e-Learning and Intelligent Help","authors":"K. Kabassi, M. Virvou, G. Tsihrintzis","doi":"10.1142/9789812797025_0004","DOIUrl":"https://doi.org/10.1142/9789812797025_0004","url":null,"abstract":"","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128930058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Deep Evaluation of Two Cognitive User Models for Personalized Search 个性化搜索中两种认知用户模型的深度评价
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0002
Fabio Gasparetti, A. Micarelli
{"title":"A Deep Evaluation of Two Cognitive User Models for Personalized Search","authors":"Fabio Gasparetti, A. Micarelli","doi":"10.1142/9789812797025_0002","DOIUrl":"https://doi.org/10.1142/9789812797025_0002","url":null,"abstract":"","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132893737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Experimental Analysis of Multiattribute Utility Collaborative Filtering on a Synthetic Data Set 合成数据集上多属性效用协同过滤的实验分析
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0005
N. Manouselis, C. Costopoulou
{"title":"Experimental Analysis of Multiattribute Utility Collaborative Filtering on a Synthetic Data Set","authors":"N. Manouselis, C. Costopoulou","doi":"10.1142/9789812797025_0005","DOIUrl":"https://doi.org/10.1142/9789812797025_0005","url":null,"abstract":"","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133543930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
User Acceptance of Knowledge-based Recommenders 用户对基于知识的推荐的接受程度
Personalization Techniques and Recommender Systems Pub Date : 1900-01-01 DOI: 10.1142/9789812797025_0010
A. Felfernig, E. Teppan, B. Gula
{"title":"User Acceptance of Knowledge-based Recommenders","authors":"A. Felfernig, E. Teppan, B. Gula","doi":"10.1142/9789812797025_0010","DOIUrl":"https://doi.org/10.1142/9789812797025_0010","url":null,"abstract":"Recommender applications support decision-making processes by helping online customers to identify products more effectively. Recommendation problems have a long history as a successful application area of Artificial Intelligence (AI) and the interest in recommender applications has dramatically increased due to the demand for personalization technologies by large and successful e-Commerce environments. Knowledgebased recommender applications are especially useful for improving the accessibility of complex products such as financial services or computers. Such products demand a more profound knowledge from customers than simple products such as CDs or movies. In this paper we focus on a discussion of AI technologies needed for the development of knowledgebased recommender applications. In this context, we report experiences from commercial projects and present the results of a study which investigated key factors influencing the acceptance of knowledge-based recommender technologies by end-users.","PeriodicalId":329425,"journal":{"name":"Personalization Techniques and Recommender Systems","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122367741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
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