A Linear General Type-2 Fuzzy-Logic-Based Computing With Words Approach for Realizing an Ambient Intelligent Platform for Cooking Recipe Recommendation

Abstract

Abstract-This paper addresses the need to enhance transparency in Ambient Intelligent Environments by developing more natural ways of interaction, which allow the users to communicate easily with the hidden networked devices rather than embedding obtrusive tablets and computing equipment throughout their surroundings. Ambient Intelligence vision aims to realize digital environments that adapt to users in a responsive, transparent and context aware manner in order to enhance users' comfort. It is therefore appropriate for employing the paradigm of 'Computing With Words' (CWWs), which aims to mimic the ability of humans to communicate transparently and manipulate perceptions via words. One of the daily activities that would increase the comfort levels of the users (especially people with disabilities) is cooking and performing tasks in the kitchen. Existing approaches on food preparation, cooking, and recipe recommendation stress on healthy eating and balanced meal choices while providing limited personalization features through the use of intrusive user interfaces. Herein, we present an application, which transparently interacts with users based on a novel CWWs approach in order to predict the recipe's difficulty level and to recommend an appropriate recipe depending on the user's mood, appetite and spare time. The proposed CWWs framework is based on Linear General Type-2 (LGT2) Fuzzy Sets, which linearly quantify the linguistic modifiers in the third dimension in order to better represent the user perceptions while avoiding the drawbacks of type-1 and interval type-2 fuzzy sets. The LGT2 based CWWs framework can learn from user experiences and adapt to them in order to establish more natural human-machine interaction. improvement when general type-2 fuzzy sets are used than when interval type-2 fuzzy sets are used instead. The quantitative and qualitative analysis both show the success of the system in providing a natural interaction with the users for recommending food recipes where the quantitative analysis shows the high statistical correlation between the system output and the users' feedback; and the qualitative analysis presents social science evaluation confirming the strong user acceptance of the system. Index Terms-ambient intelligence, computing with words, general type-2 fuzzy sets I. INTRODUCTIONhe recent years have witnessed a rapid increase in the miniaturization of computers which enabled to embed computing throughout our spaces in familiar objects such as home appliances (e.g. washing machines, refrigerators, etc.), portable devices (e.g. mobile phones, tablets, etc.), cars, etc. In addition, the advances in communications allowed such devices to be networked and connected to the Internet. Among the highlights of the connected and miniaturized devices bring to real life is the opportunity of customization and therefore personalization. Lately, it is getting more important to deliver personalized content in areas such as food planning which is becoming an important personal issue that affects the ...

Enhanced linguistic computational models and their similarity with Yager’s computing with words

“…where 𝐼 𝑇 𝑗𝑝 , 𝑝 = 1, … , 𝑖, 𝐼 𝑇 𝑗ℎ , ℎ = 2, … , 𝑖 are the indices 3 of the linguistic terms given in Eq. (8) and…”

“…Computing with Words (CWW) [5][6][7][8], [13], [20][21][22], [30], was conceptualized by Prof. Zadeh in his seminal work [41]. According to Prof. Zadeh, CWW [41], [43], [45] is a novel data processing methodology that aims to impart the machines with a capability, such that machines can process the linguistic information (LI) seamlessly like human beings do.…”

A review on stability analysis of continuous-time fuzzy-model-based control systems: From membership-function-independent to membership-function-dependent analysis

“…In (15), the order of fuzzy summations is 2 as the product term of membership functions involves two membership functions, e.g., w i w j . In the following, multiplying p k=1 w k which equals 1 due to the property of membership functions in (3), to the left hand side of (15) gives below:…”

“…With the support of fuzzy set theory and mathematics, a fuzzy logic system can perform reasoning according to the designated linguistic rules. Fuzzy logic systems were used successfully in a wide range of areas and applications [2,3,4] such as assessment [5], classification [6,7,8], control [9,10,11], decision making [12,13,14,15,16,17], evaluation [18,19], forecasting [20,21,22], learning [23,24,25], modeling [26,27] and etc.…”

A gentle introduction and survey on Computing with Words (CWW) methodologies

“…Theoretical works on perceptual computing are [25][26][27][28][29][30][31][32][33][34][35]. The LFSCM has been applied for cooking recipe recommendations in Ambient Intelligent Environments [8,36,37]. Other research works on the LFSCM are [38][39][40][41][42].…”