A fuzzy conceptualization model for text mining with application in opinion polarity classification

A comprehensive survey on formal concept analysis, its research trends and applications

“…Subsequently, FCA is extended into different Mining similar concepts Aswani Kumar, 2011b Knowledge discovery Aswani Kumar, 2012 Rule mining Belohlavek et al, 2011aIPAQ questionnaires Belohlavek et al, 2013b Background knowledge Dau, 2013 Analyzing a triple store Fowler, 2013 Order in taxonomy Galitsky et al, 2013 Pattern on parse thickets Macko, 2013 Fuzzy FCA Missaoui and Kwuida, 2011 Triadic rules Nguyen et al, 2011 Mathematical search Nguyen and Yamamoto, 2012 Learning from graph Li et al, 2011b Symbolic data analysis Pavlovic, 2012 Quantitative data analysis Rouane et al, 2013 Multi relational data Li and Tsai, 2013 Sentiments analysis Trabelsi et al, 2012 Analyzing folksonomies Vityaev et al, 2012 Probabilistic concepts Watmough, 2014 ERP analysis Yang et al, 2011b Decision-making Zhao and Liu, 2011…”

“…The ingredients of FCA with mathematical morphology and description logics have been combined for image processing tasks by Atif et al (2014). We observe that some of the researchers have tried to analyze the sentiments of people using FCA (emotions, love, preference) (Li and Tsai, 2013;Antoni et al, 2014). The word opinion or preference shows two sides: one is acceptation and another is non-acceptation, which may mold the concept lattice for bipolar information visualization (Singh and Aswani Kumar, 2014).…”

“…Other domains discuss the mathematics behind FCA with a fuzzy setting, an interval-valued fuzzy setting, possibility theory, a rough setting, a triadic, factor and incomplete context to apply these extensions in the appropriate context for knowledge processing tasks. Ferjani et al, 2012Feature extractions Formica, 2012 Semantic web Galitsky et al, 2013 Finding patterns on parse thickets Hamrouni et al, 2013 Finding some frequent itemset Li and Guo, 2013 Investigating formal query De Maio et al, 2014 Text mining Muangprathub et al, 2013 Classification Li andTsai, 2013 Text mining Finding cousins Neznanov and Kuznetsov, 2013 FCART tool Poshyvanyk et al, 2012 Concept location Priss, 2006 Application in information sciences Senatore and Pasi, 2013 Finding correlations Li and Tsai, 2013 Opinion classification Zerarga and Djouadi, 2013 Information retrieval Military intelligence Du and Hai, 2013 Mining web page Elzinga et al, 2010 Terrorist threat assessment Poelmans et al, 2013c Criminal trajectories Priss, 2011 Unix system monitoring Romanov et al, 2012 Detect anomalies Web services…”

“…Research goal Antoni et al, 2014 Preference analysis Li and Tsai, 2013 Opinion classification Poelmans, 2011 Domestic violence Priss, 2006 Information science Spoto et al, 2010 Computerized psychological assessment using FCA …”

Document Classification System According to the Degree of Semantic Link Expressed Fuzzy Function

“…Another problem is that there is a limitation in reflecting the user's interest due to a relatively simple learning process. [9][10][11] To overcome these limitations, this study proposes using fuzzy membership function for denoting the occurrence frequency of the extracted key words by means of the extent of significance of the key word in the document. In addition to this, the fuzzy relation is also applied in order to take advantage of document classification technique by which a set of documents semantically interconnected will be classified into the same group of documents.…”