Browsing by Author "Lin, Lien-Fa"

Now showing 1 - 9 of 9

A diffusion planning mechanism for social marketing
(2017-07-01)
Li, Yung-Ming
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Lai, Cheng-Yang
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Lin, Lien-Fa
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Social media is gaining importance as a component of marketing strategies. Many types of social media, such as social networking sites, blogospheres and micro-blogospheres, have been seeking business opportunities and establishing brand expression in the recent years. Online marketing information diffusion has become the critical business model of online social networks. However, most of the current marketing studies on discovering potential influences do not appropriately support them to diffuse advertisements. Therefore, marketing information may be lost during the diffusion process and cannot be sent to potential customers successfully. In this research, a diffusion path planning mechanism for advertisements is developed to help influencers to propagate marketing information and help marketers to evaluate possible rewards under different marketing strategies. Our experimental results show that the proposed mechanism can significantly improve the diffusion process of advertising messages and decrease marketing uncertainty. (C) 2016 Elsevier B.V. All rights reserved.
A recommender mechanism for social knowledge navigation in an online encyclopedia
(2014-09-01)
Li, Yung-Ming
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Lin, Lien-Fa
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Lin, Yu-Hui
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
In today\'s world, knowledge is important for constructing core competitive advantages for individuals and organizations. Recently, Web 2.0 applications and social media have provided a convenient medium for people to share knowledge over the Internet. However, the huge amount of created knowledge can also leads to the problem of information overload. This research proposes a social knowledge navigation mechanism that utilizes the techniques of relevant knowledge network construction, knowledge importance analysis, and knowledge concept ontology construction to generate a visualized recommendation of a knowledge map of sub-concept and knowledge of an article reading sequence for supporting learning activities related to a free online encyclopedia. The results of experiments conducted on Wikipedia show that the proposed mechanism can effectively recommend useful articles and improve a knowledge seeker\'s learning effectiveness. (C) 2014 Elsevier Ltd. All rights reserved.
A social endorsing mechanism for target advertisement diffusion
(2015-12-01)
Lin, Lien-Fa
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Li, Yung-Ming
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Wu, Wen-Hsiang
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Social media plays an increasingly important role in people\'s daily lives and attracts companies to conduct marketing activities. Determining how to effectively utilize this new media to distribute promotional advertisements to suitable customers is thus an important issue. In this research, an endorser-based social diffusing mechanism, which considers the factors of users\' preferences, influence, and diffusion power, is proposed to enhance the effectiveness of target advertising by discovering the most appropriate endorsers that can propagate the ads to the identified target users. Our experimental results show the proposed model can appropriately enhance satisfaction and target delivery rate. (C) 2015 Elsevier B.V. All rights reserved.
A social recommendation mechanism for enhancing 020 e-commerce
(2017-01-01)
Lin, Lien-Fa
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Li, Yung-Ming
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
O2O business model synergize the efficiency improved from online retailing and value created from physical customer experience. Nowadays, while many O2O apps and services have been proposed, the study of the accuracy of customer targeting and the effectiveness of advertising in a dynamic environment are big challenges currently faced by O2O e-commerce. In this paper, we proposed a novel social recommendation mechanism for enhancing O2O e-commerce, by incorporating the techniques of context-awareness and social referral. The proposed mechanism could identify the most suitable ads for targeted users in a changing environment, and could significantly improve the effectiveness of advertising by taking the influence of friends into consideration.
A social recommender mechanism for location-based group commerce
(2014-08-01)
Li, Yung-Ming
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Chou, Chia-Ling
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Lin, Lien-Fa
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
With the rapid growth of social media platforms, numerous group commerce websites, which exploit both the advantages of price discounts and experience value, have emerged. Moreover, the popularity of sophisticated mobile devices brings great commercial opportunities for local store to gain publicity. In this research, considering user preference, geographic convenience, and friends\' influence, a group-coupon recommender system is proposed for promoting location-sensitive products. The results of experiments conducted on Facebook indicate that the proposed mechanism could accurately recommend products and satisfactorily provide a companion list of to customers, significantly increasing willingness to purchase by taking advantage of the power of social influence. (C) 2014 Elsevier Inc. All rights reserved.
A social referral appraising mechanism for the e-marketplace
(2017-04-01)
Lai, Cheng-Yang
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Li, Yung-Ming
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Lin, Lien-Fa
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
With the popularity of social media, in order to achieve word-of-mouth marketing, many marketers and individual sellers are actively engaged in achieving positive ratings in the e-marketplace. Although many seller review mechanisms have been developed, e-commerce market operators and consumers still face trust fraud issues. Trust is one of the major issues that confuse online purchase activities. In this paper, we develop a social referral mechanism to verify sellers based on the experiences of friends within a buyer's social network. The proposed framework estimates the trust values of sellers from the perspective of the social network in order to stop buyers from making transactions with fraudulent sellers in the online marketplace. (C) 2016 Elsevier B.V. All rights reserved.
A social route recommender mechanism for store shopping support
(2017-02)
Li, Yung-Ming
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Lin, Lien-Fa
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Ho, Chun-Chih
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
To survive in a fiercely competitive business environment, it has become increasingly important for physical retailers to provide customers with services offering a better shopping experience. Many renovate and enlarge their shopping spaces to make their stores more enjoyable places to visit. The growth in social media and the use of mobile devices provide retailers with an opportunity to offer a context-aware guidance service to enhance customers\' in-store shopping experience. In this research, by extracting and analysing shopping information (shopping context, visiting trajectory) and social information (user\'s interest, friends\' influence), a contextual store shopping recommendation system is proposed to provide an appropriate route for first-time customers or those who are unfamiliar with a retailer\'s shopping space. Our experimental results show that the proposed model is effective in providing an appropriate shopping route and enhancing users\' shopping experience, which could significantly improve the profitability and competitive advantage of the retailers. (C) 2016 Elsevier B.V. All rights reserved.
Creating social intelligence for product portfolio design
(2014-10-01)
Li, Yung-Ming
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Chen, Hsuan-Ming
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Liou, Jyh-Hwa
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Lin, Lien-Fa
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資訊管理與財務金融系註：原資管所+財金所
Increasing numbers of people are using social media to express their personal experiences. Recently, these plentiful user-generated data sources have been utilized promisingly by enterprises for product creation. In this research, we propose a social intelligence mechanism that can extract and consolidate the reviews expressed via social media and derive insights (product feature specification and feature importance) to help enterprises make decisions on developing next-generation products by analyzing the reviewers\' knowledge and authority and their opinion sentiment toward the target products. The experimental results obtained using Epinions.com show that the proposed mechanism outperforms other benchmark approaches in market trend prediction and customer acceptance. (C) 2014 Elsevier B.V. All rights reserved.
SEARCH LOCATION-DEPENDENT DATA IN BROADCASTING ENVIRONMENT
(2009)
Lin, Lien-Fa
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Li, Yung-Ming
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Location-based services (LBSs) provide the information based oil location information as specified in a query. Queries that support LBS are called Location-Dependent Queries (LDQ). LDQ contain: range query. nearest neighbor (NN) query, k-nearest neighbor (KNN) query and reverse nearest neighbor (RNN) query. Examples of mobile LBSs include location-dependent information access (e.g.. traffic reports and attractions) and nearest neighbor queries (e.g. finding the nearest restaurant). While LDQ is well studied in the traditional wired, disk-based client-server environment. it has not yet been tackled in relation to a wireless broadcasting environment. In this paper. the issues involved with organizing location-dependent data and answering LDQ queries on the air. are investigated. The linear properly of wireless broadcasting media and the power conservation requirement of mobile devices make the problem particularly interesting and challenging. An efficient data organization, called Jump R(Inn-Tree. and the corresponding search algorithm are proposed. The performance of the proposed Jump, is evaluated Rdnn-Tree and other traditional indexes (enhanced for wireless broadcasting) by using both uniform and skew data. The result shows that Jump Rdnn-Tree substantially outperforms the traditional indexes.