Towards a Temporal Extension of Formal Concept analysis

Neouchi, Rabih; Tawfik, Ahmed Y.; Frost, Richard A.

doi:10.1007/3-540-45153-6_33

Cited by 11 publications

(13 citation statements)

References 2 publications

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“…In literature, some approaches that extend formal concept analysis to handle temporal properties and represent temporally evolving attributes exist [22].…”

Section: Take -Time Aware Knowledge Extractionmentioning

confidence: 99%

Time Aware Knowledge Extraction for microblog summarization on Twitter

et al. 2016

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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.

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“…In literature, some approaches that extend formal concept analysis to handle temporal properties and represent temporally evolving attributes exist [22].…”

Section: Take -Time Aware Knowledge Extractionmentioning

confidence: 99%

Time Aware Knowledge Extraction for microblog summarization on Twitter

et al. 2016

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“…In particular, the computation of the L-fuzzy concepts associated with R (1) allows to analyze in what stores the main sales of each article during a month (independent of the month) have taken place. If we take relation R (k) with k > 1 we are relaxing the exigency taking the k greater sales for our study.…”

Section: The Fuzzy Context Sequence General Studymentioning

confidence: 99%

“…Wolff defines the Temporal Concept Analysis where a Conceptual Time System is introduced such that the state and phase spaces are defined as concept lattices which represent the meaning of the states with respect to the chosen time description. On the other hand, the authors define the hidden evolution patterns in 1,4 using temporal matching in the case of Formal Concept Analysis.…”

Section: Introductionmentioning

confidence: 99%

The study of fuzzy context sequences

Alcalde¹,

Burusco²,

Fuentes-González³

2013

IJCIS

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In some cases, the relationship between an object set X and an attribute set Y is set up by means of a fuzzy context sequence. A particular case of this situation appears when we want to study the evolution of an L-fuzzy context in time.In this work, we analyze these situations. First we introduce the fuzzy context sequence definition and remind the main results about OWA operators. With the aid of these operators, we propose an exhaustive study of the different contexts values of the sequence using some new relations. In the second part, we also study the fuzzy context sequences establishing tendencies and temporal patterns. Finally, we illustrate all the results by means of examples.

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“…We specially focus on searching trends in the evolution of the relationship between objects and attributes. Several works which consider temporal evolution in a Formal context can be found in the literature as, for instance, [33,37,38].…”

Section: Introductionmentioning

confidence: 99%

Evolution in time of L-fuzzy context sequences

Alcalde

Burusco

Bustince

et al. 2016

Information Sciences

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In this work, we consider a complete lattice L and we study L-fuzzy context sequences which represent the evolution in time of an L-fuzzy context. To carry out this study, in the first part of the paper, we consider n-ary OWA operators in complete lattices, which enable us to make a general analysis and a temporal analysis at any moment in time of L-fuzzy context sequences. After that, evolution in time of the relationship between the objects and the attributes is considered. In particular, we analyze the concepts of Trend and Persistent formal contexts. Finally, we illustrate our results with an example where we consider the particular lattice L = J ([0, 1]).

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Towards a Temporal Extension of Formal Concept analysis

Cited by 11 publications

References 2 publications

Time Aware Knowledge Extraction for microblog summarization on Twitter

Time Aware Knowledge Extraction for microblog summarization on Twitter

The study of fuzzy context sequences

Evolution in time of L-fuzzy context sequences

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