To Adapt to Changes in the User Long-Term and Recent Interest of Personalized Recommendation Model

2013 ◽  
Vol 791-793 ◽  
pp. 2143-2146 ◽  
Author(s):  
Hua Yue Chen ◽  
Jing Pu
Keyword(s):  
Recommendation System ◽  
Information Source ◽  
Information Organization ◽  
Personalized Recommendation ◽  
Web Information Retrieval ◽  
Exponential Expansion ◽  
Personalized Services ◽  
Internet Information ◽  
Information Recommendation

With the development and popularization of the information superhighway, people are surrounded by the sea of information. Exponential expansion of Internet information resources, is the vast amounts of information source, its information organization is heterogeneous, diverse, distribution and other features. therefore, can provide users with effective information recommendation, help users to find the valuable information you need the personalized recommendation system won wide attention in the field of Web information retrieval, and also in actual personalization service system has been widely applied in this paper, the personalized services recommendation system architecture to do some research, proposed a distinguishing the user long-term interests and immediate interests provide information to recommend a new model of personalized recommendation.

The Design and Implementation of E-Commerce Personalized Services Based on Collaborative Filtering Recommendation System

2014 ◽  
Vol 687-691 ◽  
pp. 2039-2042 ◽  
Author(s):  
Meng Han
Keyword(s):  
Collaborative Filtering ◽  
Recommendation System ◽  
Reference Value ◽  
Personalized Recommendation ◽  
Site Management ◽  
Logical Model ◽  
Recommendation Algorithm ◽  
Design And Implementation ◽  
Personalized Services

In this paper, in accordance with the need of e-commerce site management, constructing the logical model of the personalized recommendation system, and use filtering recommendation algorithm to design the personalized recommendation engine. It is necessary to provide certain reference value to improve the personalized recommendation efficiency of e-commerce sites.

scholarly journals An Algorithm for Generating a Recommended Rule Set Based on Learner's Browse Interest

2018 ◽  
Vol 13 (11) ◽  
pp. 102
Author(s):  
Xiaowei Hao ◽  
Shanshan Han
Keyword(s):  
Association Rule ◽  
Quantitative Relationship ◽  
Personalized Recommendation ◽  
Current Interest ◽  
Quality Of Information ◽  
Rule Set ◽  
Information Recommendation ◽  
Browsing Behavior

To personalize the recommended learning information according to the interests of the learner, a recommendation rule set generation algorithm based on learner browsing interests was proposed. First, the learner's browsing behavior was captured. A multivariate regression method was used to calculate the quantitative relationship between the learner's browsing behavior and the degree of interest in the web page to generate a learner's current interest view (CIV). With this current interest view, a content-based collaborative filtering personalized information recommendation service was provided to learners. Then, a new weighted association rule algorithm was used to discover the associations between the items, so that the degree of recommendation was obtained. Furthermore, the degree of recommendation was used as a personalized recommendation service for learners with long-term interests. The results showed that the proposed algorithm effectively improved the quality of information recommendation and the real-time performance of the recommendation. Therefore, this algorithm has a good application value in the field of personalized learning recommendation.

Mobile E-Commerce Personalized Information Recommendation Model

2014 ◽  
Vol 687-691 ◽  
pp. 2136-2139
Author(s):  
Yue Ming Wang ◽  
Rui Li Wang ◽  
De Xun Xu
Keyword(s):  
Recommendation System ◽  
Large Data ◽  
Important Application ◽  
Mobile Internet ◽  
System Model ◽  
Personalized Recommendation ◽  
Mobile Business ◽  
Commercial Activities ◽  
Information Recommendation ◽  
Work And Life

In recent years, the mobile Internet got swift and violent development, business gradually permeate into almost every a of people's work and life, personalized recommendation system model has important application value in mobile commercial activities, this article expounds the mobile commercial personalized recommendation model, and analyzed its structure, discussed the method of using cloud computing for mobile business and the necessity of large data processing.

scholarly journals Evaluation of Recommendation System for Sustainable E-Commerce: Accuracy, Diversity and Customer Satisfaction

2020 ◽  
Author(s):  
Qinglong Li ◽  
Ilyoung Choi ◽  
Jaekyeong Kim
Keyword(s):  
Customer Satisfaction ◽  
Deep Neural Networks ◽  
Recommendation System ◽  
Personalized Recommendation ◽  
Sustainable Competitive Advantage ◽  
Customer Data ◽  
The Sustainable Development ◽  
Personalized Services ◽  
Recommendation Algorithms ◽  
Positive Effect

With the development of information technology and the popularization of mobile devices, collecting various types of customer data such as purchase history or behavior patterns became possible. As the customer data being accumulated, there is a growing demand for personalized recommendation services that provide customized services to customers. Currently, global e-commerce companies offer personalized recommendation services to gain a sustainable competitive advantage. However, previous research on recommendation systems has consistently raised the issue that the accuracy of recommendation algorithms does not necessarily lead to the satisfaction of recommended service users. It also claims that customers are highly satisfied when the recommendation system recommends diverse items to them. In this study, we want to identify the factors that determine customer satisfaction when using the recommendation system which provides personalized services. To this end, we developed a recommendation system based on Deep Neural Networks (DNN) and measured the accuracy of recommendation service, the diversity of recommended items and customer satisfaction with the recommendation service. The experimental results of is the study showed that both recommendation system accuracy and diversity would have a positive effect on customer satisfaction. These results can further improve customer satisfaction with the recommendation system and promote the sustainable development of e-commerce.

Research on the Application of Agent in Personalized Information Recommendation System

2011 ◽  
Vol 271-273 ◽  
pp. 853-856
Author(s):  
Dan Er Chen
Keyword(s):  
Recommendation System ◽  
Word Of Mouth ◽  
Information Overload ◽  
Daily Life ◽  
Social Process ◽  
Information Services ◽  
Personalized Recommendation ◽  
Agent Systems ◽  
Information Recommendation

In daily life, we rely on other people's suggestions or by word of mouth or recommendation letters and book reviews printed in newspapers and general surveys, such as restaurant guides. However, the Internet's explosive growth has brought us information that anyone can be greatly difficult to digest. To cope with the flood of information, the personalized recommendation systems have been established to assist and complement the natural social process. These systems recommend users to select information that users may be interested in and filter out which users may not be interested. In order to alleviate the information overload problem, the author researches on the application of agent in personalized information recommendation system. The system collects user information of interest through the agent systems and queries the resources to filter and remove information that users do not need. It can provide users with intelligent and active information services.

scholarly journals A Study on Information Technology Freelancer Matching with Exploiting Blockchain in Gig Economy

2021 ◽  
Vol 18 ◽  
pp. 455-461
Author(s):  
Jinho Lim ◽  
Kwansik Na ◽  
Seungcheon Kim
Keyword(s):  
Recommendation System ◽  
Service Providers ◽  
High Reliability ◽  
Information Source ◽  
Reputation System ◽  
Personalized Recommendation ◽  
Blockchain Technology ◽  
Gig Economy ◽  
User Reputation ◽  
Recruitment System

In this paper, we propose a freelancer matching of a recommended recruitment system in a situation in which the freelance type employment market defined by peer-to-peer transactions, mutual evaluation of freelancers and clients, time flexibility of service providers, and the use of service providers' tools and assets are expanding. In order to increase the reliability and accuracy of recommendation through reputation, we propose a reputation ranking technique for reputation system, which is a kind of personalized recommendation system, based on the blockchain technology. We propose a reputation system model suitable for recruitment matching service. We have aims to study the method of implicitly extracting user reputation information based on two factors suitable for word of mouth among information source reliability factors. In other words, this paper defines a method for automatically extracting two reliability factors of freelancers from past reputation information, and proposes a method for effectively predicting freelancer applicant’ reputation information using only the information of high-reliability evaluators.

The use of a bespoke website developed for people with dementia and carers: Users’ experiences, perceptions and support needs

Dementia ◽  
2021 ◽  
pp. 147130122110284
Author(s):  
Emma Wolverson ◽  
Caroline White ◽  
Rosie Dunn ◽  
Katie Cunnah ◽  
David Howe ◽  
...  
Keyword(s):  
Personal Information ◽  
Information Source ◽  
Website Design ◽  
Long Term Conditions ◽  
People With Dementia ◽  
Barriers To Use ◽  
Credible Information ◽  
Training And Support ◽  
Design And Methods

Background: Current policy emphasises the role of digital technologies in facilitating the management of long-term conditions. While digital resources have been developed for carers, there has been little attention to their development for people with dementia. The Caregiverspro-MMD website was developed as a joint resource for people with dementia and carers, delivering access to information, informal content, games and peer support. Research Design and Methods: This study explored the experiences of dyads consisting of people with dementia and carers of using the website. Interviews and focus groups were conducted with 43 participants. Findings: Thematic analysis identified 10 subthemes grouped under three superordinate themes which highlight participants’ experiences of and responses to the website functions; important aspects of the website design and delivery; and barriers to use. Discussion: Findings highlight the value of a credible information source which negated the need for arduous online searches, the pleasure associated with playing games and interacting with others online. However, participants were reluctant to share personal information online, preferring to create ‘informal content’ which celebrated everyday life, and were reluctant to ‘friend’ people online who they had not met in person. The importance of training and support to use the website was highlighted. Health problems, lack of interest or difficulties using technology, and time were all identified as barriers to use.

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