Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis

Maio, Carmen De; Fenza, Giuseppe; Loia, Vincenzo; Senatore, Sabrina

doi:10.1016/j.ipm.2011.04.003

Cited by 88 publications

(28 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 3 represents a fuzzy formal context in which the number of objects ( i O )  number of attributes ( j A ) (Case 1) [8]. Table 4 represents the corresponding crisp context of Table 3 using the proposed method.…”

Section: Illustration Of the Proposed Methodsmentioning

confidence: 99%

“…Prade [25] Aswani Kumar Bartl et al [41] Skowron et al [44] For detailed illustrations about generating the formal concepts from a given formal context, readers can refer to references including [1][2][3][4][5][6][7][8]13,16,[24][25][26][27][29][30][31][32][33][34][35][36][37][38][39][40]. Reducing the number of formal concepts and the size of the lattice structure are open issues for researchers as knowledge reduction problems.…”

Section: Formal Concept Analysis In the Fuzzy Settingmentioning

confidence: 99%

See 1 more Smart Citation

A Note on Computing the Crisp Order Context of a Fuzzy Formal Context for Knowledge Reduction

Singh¹,

Cherukuri²

2014

J Inf Process Syst

View full text Add to dashboard Cite

Fuzzy Formal Concept Analysis (FCA) is a mathematical tool for the effective representation of imprecise and vague knowledge. However, with a large number of formal concepts from a fuzzy context, the task of knowledge representation becomes complex. Hence, knowledge reduction is an important issue in FCA with a fuzzy setting. The purpose of this current study is to address this issue by proposing a method that computes the corresponding crisp order for the fuzzy relation in a given fuzzy formal context. The obtained formal context using the proposed method provides a fewer number of concepts when compared to original fuzzy context. The resultant lattice structure is a reduced form of its corresponding fuzzy concept lattice and preserves the specialized and generalized concepts, as well as stability. This study also shows a step-by-step demonstration of the proposed method and its application.

show abstract

Section: Illustration Of the Proposed Methodsmentioning

confidence: 99%

Section: Formal Concept Analysis In the Fuzzy Settingmentioning

confidence: 99%

A Note on Computing the Crisp Order Context of a Fuzzy Formal Context for Knowledge Reduction

Singh¹,

Cherukuri²

2014

J Inf Process Syst

View full text Add to dashboard Cite

show abstract

“…This work presents the Time Aware Knowledge Extraction (briefly TAKE) methodology, as a new approach to perform conceptual and temporal data analysis of tweets' content for microblog summarization. TAKE extends Fuzzy Formal Concept Analysis [10] introducing time dependencies among objects, in order to provide a summary that follow the evolution of the story over the timeline. Furthermore, the proposed framework reveals good performances in terms of F-Measure, with optimal Recall and comparable values of Precision with respect to the compared approaches.…”

Section: Related Workmentioning

confidence: 99%

“…Secondly, it is possible to identify temporal peaks of tweet frequency analyzing timestamps and exploiting the Offline Peak-Finding Algorithm (OPAD), proposed in [9]. Then, taking into account the meaning of the tweet content and time dependences among detected peaks, temporal extension of Fuzzy Formal Concept Analysis [10,11] will be performed in order to arrange tweets into a hierarchy of time dependent concepts, that is a timed fuzzy lattice. Finally, a summarization algorithm has been defined exploring resulting timed fuzzy lattice knowledge structure.…”

Section: Introductionmentioning

confidence: 99%

Time Aware Knowledge Extraction for microblog summarization on Twitter

et al. 2016

Self Cite

View full text Add to dashboard Cite

Microblogging services like Twitter and Facebook collect millions of user generated content every moment about trending news, occurring events, and so on.Nevertheless, it is really a nightmare to find information of interest through the huge amount of available posts that are often noise and redundant. In general, social media analytics services have caught increasing attention from both side research and industry. Specifically, the dynamic context of microblogging requires to manage not only meaning of information but also the evolution of knowledge over the timeline. This work defines Time Aware Knowledge Extraction (briefly TAKE) methodology that relies on temporal extension of Fuzzy Formal Concept Analysis. In particular, a microblog summarization algorithm has been defined filtering the concepts organized by TAKE in a time-dependent hierarchy. The algorithm addresses topic-based summarization on Twitter. Besides considering the timing of the concepts, another distinguish feature of the proposed microblog summarization framework is the possibility to have more or less detailed summary, according to the user's needs, with good levels of quality and completeness as highlighted in the experimental results.

show abstract

“…Specifically, the fuzzy extension of Formal Concept Analysis, i.e., Fuzzy FCA [4], is applied. This step takes, as input, the vectors of words created in the previous steps (Natural Language Processing and Vectorization) and constructs the fuzzy formal context.…”

Section: Fig 1 Taxonomy Buildingmentioning

confidence: 99%

Automatic Generation of SKOS Taxonomies for Generating Topic-Based User Interfaces in MOOCs

Maio

Loia

Mangione

et al. 2014

Open Learning and Teaching in Educational Communities

Self Cite

View full text Add to dashboard Cite

Abstract. The aim of the paper is to provide a framework for the automatic generation of topic-based user interfaces for video lectures in MOOCs. The proposed approach leverages on Fuzzy Formal Concept Analysis and Semantic Technologies, which allow the definition of solutions for supporting learners to navigate the fragments of one or more video lectures, by selecting the topics of interest. The exploitation of a Semantic Web vocabulary, namely SKOS, to model topics, and their relationships, enables the interconnection of different video lectures, also belonging to different MOOCs. The high interoperability allowed by Semantic Web technologies enables the integration of different and heterogeneous MOOC Platforms, as well as other Open Repositories. This aspect fosters the capability of learners to self-regulate and to enhance their learning paths in new forms of learning experiences based on exploration.

show abstract

Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis

Cited by 88 publications

References 17 publications

A Note on Computing the Crisp Order Context of a Fuzzy Formal Context for Knowledge Reduction

A Note on Computing the Crisp Order Context of a Fuzzy Formal Context for Knowledge Reduction

Time Aware Knowledge Extraction for microblog summarization on Twitter

Automatic Generation of SKOS Taxonomies for Generating Topic-Based User Interfaces in MOOCs

Contact Info

Product

Resources

About