Application of Fuzzy Ontology to Information Retrieval for Electronic Commerce

Zhai, Jun; Shen, Lianfeng; Liang, Yiduo; Jiang, Jiatao

doi:10.1109/isecs.2008.177

Cited by 15 publications

(5 citation statements)

References 7 publications

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“…An alternative to probabilistic ontologies are fuzzy ontologies, defined with several purposes, depending on the kind of imperfection they need to represent and manage in the application [47]. Samani and Shamsfard [48] distinguish the definitions of fuzzy ontologies into three main categories: those including just fuzzy relationships [49][50][51][52] or fuzzy attributes [53]; those including both fuzzy attributes and fuzzy relationships [54]; and those including fuzzy attributes, fuzzy relationships and fuzzy axioms defined by fuzzy IF-THEN rules admitting a degree of truth [12,55].…”

Section: Ontologies and Soft Ontologiesmentioning

confidence: 99%

A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

Bordogna¹

2021

Information

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The paper analyses the characteristics of Volunteer Geographic Information (VGI) and the need to assure and assess its quality for a possible use and re-use. Ontologies and soft ontologies are presented as means to support quality assurance and assessment of VGI by highlighting their limitations. A proposal of a possibilistic approach using fuzzy ontology is finally illustrated that allows to model both imprecision and vagueness of domain knowledge and epistemic uncertainty affecting observations. A case study example is illustrated.

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Section: Ontologies and Soft Ontologiesmentioning

confidence: 99%

A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

Bordogna¹

2021

Information

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“…FO is a generalization of crisp ontology (CO) where fuzzy relations exist between crisp concepts. FO have been successfully implemented in several application areas such as news summarization, diet recommendation, flight booking, information retrieval, reputation management, collision avoidance, and knowledge mobilization …”

Section: Introductionmentioning

confidence: 99%

Using Fuzzy Ontology to Improve Similarity Assessment: Method and Evaluation

Safaeipour

Zarandi

Bastani

2017

Int. J. Intell. Syst.

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Assessing semantic similarity is a fundamental requirement for many AI applications. Crisp ontology (CO) is one of the knowledge representation tools that can be used for this purpose. Thanks to the development of semantic web, CO‐based similarity assessment has become a popular approach in recent years. However, in the presence of vague information, CO cannot consider uncertainty of relations between concepts. On the other hand, fuzzy ontology (FO) can effectively process uncertainty of concepts and their relations. This paper aims at proposing an approach for assessing concept similarity based on FO. The proposed approach incorporates fuzzy relation composition in combination with an edge counting approach to assess the similarity. Accordingly, proposed measure relies on taxonomical features of an ontology in combination with statistical features of concepts. Furthermore, an evaluation approach for the FO‐based similarity measure named as FOSE is proposed. Considering social network data, proposed similarity measure is evaluated using FOSE. The evaluation results prove the dominance of proposed approach over its respective CO‐based measure.

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“…Image data has strong impact on consumer attention that has kindled the buying intention of consumers [1,2]. Advent of globalization has rapidly influenced the customer preferences and demands [3].…”

Section: Introductionmentioning

confidence: 99%

Retrieval Architecture with Classified Query for Content Based Image Recognition

Das

Thepade²,

Bhattacharya

et al. 2016

Applied Computational Intelligence and Soft Computing

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The consumer behavior has been observed to be largely influenced by image data with increasing familiarity of smart phones and World Wide Web. Traditional technique of browsing through product varieties in the Internet with text keywords has been gradually replaced by the easy accessible image data. The importance of image data has portrayed a steady growth in application orientation for business domain with the advent of different image capturing devices and social media. The paper has described a methodology of feature extraction by image binarization technique for enhancing identification and retrieval of information using content based image recognition. The proposed algorithm was tested on two public datasets, namely, Wang dataset and Oliva and Torralba (OT-Scene) dataset with 3688 images on the whole. It has outclassed the state-of-the-art techniques in performance measure and has shown statistical significance.

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Application of Fuzzy Ontology to Information Retrieval for Electronic Commerce

Cited by 15 publications

References 7 publications

A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

Using Fuzzy Ontology to Improve Similarity Assessment: Method and Evaluation

Retrieval Architecture with Classified Query for Content Based Image Recognition

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