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Intelligent Information Retrieval Using Hybrid of Fuzzy Set and Trust

Suruchi Chawla
- 20 Jun 2017 - 
- Vol. 10, Iss: 2, pp 311-325
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This article is published in Oriental journal of computer science and technology.The article was published on 2017-06-20 and is currently open access. It has received 1 citations till now. The article focuses on the topics: Neuro-fuzzy & Fuzzy set.

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Application of hybrid of Fuzzy Set, Trust and Genetic Algorithm in query log mining for effective Information Retrieval

TL;DR: In this paper, a hybrid of Fuzzy Set, Genetic Algorithm (GA) and Trust has been used together in query log mining for personalized web search based on using fuzzy queries for recommendation of optimal set of trusted documents.
References
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Journal ArticleDOI

What Trust Means in E-Commerce Customer Relationships: An Interdisciplinary Conceptual Typology

TL;DR: This paper justifies a parsimonious interdisciplinary typology and relates trust constructs to e-commerce consumer actions, defining both conceptual-level and operational-level trust constructs.
Proceedings ArticleDOI

Supporting trust in virtual communities

TL;DR: In this article, a trust model that is grounded in real-world social trust characteristics, and based on a reputation mechanism, or word-of-mouth, is proposed for the virtual medium.
Proceedings ArticleDOI

Trust-aware recommender systems

Paolo Massa, +1 more
TL;DR: This work proposes to replace the step of finding similar users with the use of a trust metric, an algorithm able to propagate trust over the trust network and to estimate a trust weight that can be used in place of the similarity weight.
Proceedings ArticleDOI

Trust in recommender systems

TL;DR: This paper proposes that the trustworthiness of users must be an important consideration in guiding recommendation and presents two computational models of trust and shows how they can be readily incorporated into standard collaborative filtering frameworks in a variety of ways.