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Guest Editorial Web-Based Intelligent Support Systems—Preface to the Special Section
2015
IEEE transactions on fuzzy systems
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Recently, more web-based intelligent support systems have been successfully developed and applied to various areas, including e-commerce, e-business, e-government, e-learning and e-services. ...
Web-based support systems, including web-based decision support systems and recommending systems, have enjoyed a tremendous growth and exhibited a wealth of developments. ...
Her main research interests lie in the area of decision support systems, recommender systems, prediction and early warning systems, fuzzy transfer learning, and web-based e-service intelligence. ...
doi:10.1109/tfuzz.2015.2393391
fatcat:4bcqah3ltzbgjo6sebwixei5xm
Recommendation technique-based government-to-business personalized e-services
2009
NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society
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Recommendation techniques can bring a possible solution for this issue. This study proposes a hybrid recommendation approach to provide personalized government to business (G2B) e-services. ...
A recommender system named Intelligent Business Partner Locator (IBPL) is designed to apply the proposed recommendation approach for supporting government agencies to recommend business partners. ...
Web-based personalized e-service, otherwise known as 'eservice personalization techniques', aims to provide a solution for this problem. ...
doi:10.1109/nafips.2009.5156456
fatcat:w3gj5h6ihrcpzbghcakcncyssi
Survey Paper on Web Recommendation System
2015
International Journal of Science and Research (IJSR)
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A fuzzy preference tree-based recommendation approach is then developed. ...
An item tree and user request tree-based hybrid recommendation approach is then developed. To model users' fuzzy tree-structured preferences, a fuzzy preference tree model is proposed. ...
Conclusion This paper proposes a recommendation approach for e business or e-commerce websites that have very complex product/services categories. ...
doi:10.21275/v4i11.nov151592
fatcat:xpr7efvxvbgltof33w63ln7gky
A Fuzzy Tree Matching-Based Personalized E-Learning Recommender System
2015
IEEE transactions on fuzzy systems
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Recommender systems, which aim to provide personalized recommendations for products or services, can be used to solve this issue. ...
A comprehensive case study about learning activity recommendation further demonstrates the effectiveness of the fuzzy tree matching-based personalized e-learning recommender system in practice. ...
Recommender systems, which aim to provide personalized recommendations for products or services, can be used to solve this issue. ...
doi:10.1109/tfuzz.2015.2426201
fatcat:s55c2sezbndithvb27eermla7a
Recommender system application developments: A survey
2015
Decision Support Systems
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A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management ...
(such as e-business) and application platforms (such as mobile-based platforms). ...
Because business profiles usually present complicated tree structures and users' preferences are vague and fuzzy, a fuzzy preference tree-based recommender system for personalized B2B e-services was developed ...
doi:10.1016/j.dss.2015.03.008
fatcat:y4phvn677zaondsbjkn56orxt4
E-Service Intelligence: An Introduction
[chapter]
2007
Studies in Computational Intelligence
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that are provided by e-government, e-business, e-commerce, e-market, e-finance, and e-learning systems, to name a few. ...
E-service intelligence is a new research field that deals with fundamental roles, social impacts and practical applications of various intelligent technologies on the Internet based e-service applications ...
and (5) Recommendation based e-service personalization. ...
doi:10.1007/978-3-540-37017-8_1
fatcat:wdrvcikn5fagbit4fkp7ma6nvm
A cognitive approach for agent-based personalized recommendation
2007
Knowledge-Based Systems
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There is an increasing need for various e-service, e-commerce and e-business sites to provide personalized recommendations to on-line customers. ...
A case study is included to illustrate how personalized recommendations are made by fuzzy cognitive agents in e-commerce sites. ...
to individual users of various e-service, e-commerce and e-business sites. ...
doi:10.1016/j.knosys.2006.06.006
fatcat:pqyymbtjk5gvnooebugb6c5rum
A fuzzy content matching-based e-Commerce recommendation approach
2015
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
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To well utilize the content information, this study proposed a fuzzy content matching-based recommendation approach to assist e-Commerce customers to choose their truly interested items. ...
Tree-structured content information is transformed to a set of descriptors, and users' preferences on these descriptors are derived from fuzzy ratings by using fuzzy number operations. ...
New issues also arise for modern content-based recommender systems. ...
doi:10.1109/fuzz-ieee.2015.7338036
dblp:conf/fuzzIEEE/MaoLZZ15
fatcat:o5vnljubyvfjhaiph7dgdk2j34
Developing Mobile Application for Residential Property Business in Transit-Oriented Development Areas
2020
International Journal of Technology
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Another objective of this research is to harness many mobile internet users in Indonesia, reaching 53% of the total population, to develop a mobile phone-based application that serves as the platform for ...
The proposed application has six features: My Preferences, which provides recommendations for suitable apartment units according to user preferences; Search My Apartment; My Store; Mortgage Simulation; ...
Number of family members occupying the property
unit:
a. 1 person
b. 2 persons
c. 3 persons
d. 4 persons
e. 5 persons
Table 2 2 Percentage of respondents willing to stay in the TOD area based ...
doi:10.14716/ijtech.v11i7.4481
fatcat:q23vrcf47jfspk3woy6h6hgadm
Online Shopping Decisions Enhancement with Fuzzy Expert System
2021
International Journal of Innovation in Management, Economics and Social Sciences
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To analyze the status of improvement of users' decisions, a fuzzy expert system was created using input variables business reputation status, environmental factors status in e-commerce, online store features ...
Such systems usually provide a list of suggested items that the user may prefer. These systems are provided as a support tool to help users obtain information that best meets their needs. ...
Introduction Recommender systems provide a way for personalized suggestions from existing information which can play an important role in systems such as e-commerce. ...
doi:10.52547/ijimes.1.2.84
fatcat:x7fqmryiorgg7lanvcxrp2zx6m
A fuzzy tree matching-based personalised e-learning recommender system
2014
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
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However, too many learning activities are emerging in the e-learning system, which makes it difficult for learners to select proper ones for their particular situations since there is no personalised service ...
To deal with the uncertain category issues, a fuzzy category tree and relevant similarity measure are developed. ...
Recommender systems can be defined as programs which attempt to recommend items (products and services) to users (individuals and businesses) by predicting a user's interest in a given item based on various ...
doi:10.1109/fuzz-ieee.2014.6891594
dblp:conf/fuzzIEEE/WuZL14
fatcat:2gtmat7iyjeglop4c5lqoejnx4
Toward Mobile Telecommunication Recommendation System through Intelligent Customers Categorization
2013
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
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Personalized recommendation system is needed to dynamically adapt the different customer behaviours with the most appropriate plan for them. ...
In this paper we propose a new automatic approach for costumers' categorization. This will be the basis for the recommendation system. ...
ACKNOWLEDGMENTS Our thanks to the experts who have contributed towards development of the template. Our thanks also to the developers and software engineers who contributed to the Weka project. ...
doi:10.24297/ijct.v12i7.3099
fatcat:jj7volsiarhktlypqkh4qrgi5m
A fuzzy tree similarity based recommendation approach for telecom products
2013
2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS)
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A fuzzy tree similarity based hybrid recommendation approach is proposed to solve this issue. ...
A fuzzy tree similarity measure is developed to evaluate the semantic similarity between tree structured products or user profiles. ...
Recommender Systems Recommender systems, as an important e-service intelligence method [2] , can be defined as programs which attempt to recommend items to users by predicting a user's interest in a given ...
doi:10.1109/ifsa-nafips.2013.6608505
dblp:conf/ifsa/WuZL13
fatcat:yzztalafdzazrjaljfn2fgjo5m
An Intelligent Fuzzy Rule-Based Personalized News Recommendation Using Social Media Mining
2020
Computational Intelligence and Neuroscience
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Recommendation of a relevant and suitable news article is an essential but a challenging task due to changes in the user interest categories over time. ...
To overcome the above challenges, this paper proposes fuzzy logic approach for predicting users' diversified interest and its categories by analysing their implicit user profile. ...
system-for personalized recommendation. ...
doi:10.1155/2020/3791541
pmid:32565771
pmcid:PMC7281826
fatcat:qt2y3csbxbccjbroj4fnt456he
Cloud Classroom Design for English Education Based on Internet of Things and Data Mining
2021
Mobile Information Systems
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Building an information-based teaching platform for supplementary teaching under the network environment has become a mainstream teaching method in various basic schools. ...
First of all, the system adopts a three-tier B/S model, the development platform chooses, NET, the development language, uses ASP.NET, and the database chooses SQL server. ...
to only provide a personalized path recommendation function Feel the convenience and help provided by personalized learning services. e comparison between the English classroom based on the gradient boosting ...
doi:10.1155/2021/5555006
fatcat:3uybngiqdje57kdirhwtijxf7e
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