A neural network system for transformation of regional cuisine style

We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has two characteristics. First the system can identify the degree of regional cuisine style mixture of any selected recipe and visualize such regional cuisine style mixtures using barycentric Newton diagrams. Second, the system can suggest ingredient substitutions through an extended word2vec model, such that a recipe becomes more authentic for any selected regional cuisine style. Drawing on a large number of recipes from Yummly, an example shows how the proposed system can transform a traditional Japanese recipe, Sukiyaki, into French style

Cultural Adaptation of Recipes

Building upon the considerable advances in Large Language Models (LLMs), we are now equipped to address more sophisticated tasks demanding a nuanced understanding of cross-cultural contexts. A key example is recipe adaptation, which goes beyond simple translation to include a grasp of ingredients, culinary techniques, and dietary preferences specific to a given culture. We introduce a new task involving the translation and cultural adaptation of recipes between Chinese and English-speaking cuisines. To support this investigation, we present CulturalRecipes, a unique dataset comprised of automatically paired recipes written in Mandarin Chinese and English. This dataset is further enriched with a human-written and curated test set. In this intricate task of cross-cultural recipe adaptation, we evaluate the performance of various methods, including GPT-4 and other LLMs, traditional machine translation, and information retrieval techniques. Our comprehensive analysis includes both automatic and human evaluation metrics. While GPT-4 exhibits impressive abilities in adapting Chinese recipes into English, it still lags behind human expertise when translating English recipes into Chinese. This underscores the multifaceted nature of cultural adaptations. We anticipate that these insights will significantly contribute to future research on culturally-aware language models and their practical application in culturally diverse contexts.Comment: Accepted to TAC

Makkoto umai zeyo, this is truly delicious : the social construction of taste in the region of Kōchi, Japan

La cuisine de Kōchi est bien plus qu’un moyen de subvenir à des besoins alimentaires, car c’est à la fois une manière de diviser le monde social et un atout économique. Basée sur un terrain ethnographique dans cette région rurale du Japon, cette recherche examine comment l’incorporation de croyances et les considérations pragmatiques participent à la construction sociale du goût dans la région de Kōchi. D’une part, cette recherche révèle comment l’incorporation d’éléments culturels qui sont appris, physiquement internalisés et transmis structure le monde culinaire dans cette région. L’habitus, la culture et l’identité sont quelques-uns des outils conceptuels disponibles pour analyser comment les standards gustatifs sont incorporés dans la vie quotidienne des individus. Nous goûtons littéralement le monde social au travers de nos préférences alimentaires. D’autre part, cette recherche étudie comment des considérations pragmatiques qui découlent de préoccupations matérielles immédiates contribuent à façonner la culture culinaire. Considérant que Kōchi et l’une des préfectures les plus pauvres du Japon, le besoin urgent de revitalisation incite les habitants à transformer leur cuisine en une ressource marchande. Les opportunités économiques, la planification stratégique du gouvernement et les forces du capitalisme contribuent à la création de nouveaux plats de même qu’à la promotion de saveurs traditionnelles. Ainsi, les représentations donnant un sens à l’alimentaire et les régimes de valeur attribuant un capital monétaire à l’alimentaire façonnent le palais des résidents de Kōchi. Enfin, une telle analyse doit reconnaitre que les préférences de goût (les choix que nous faisons) et la perception du goût (notre expérience sensorielle) sont fortement liées. La construction sociale du goût fait partie d’un système qui influence à la fois les choix culinaires et les sens. Un modèle analytique combinant ces deux dimensions du goût peut contribuer à une meilleure compréhension de la nature contextuelle de ce qui est jugé délicieux.The food of Kōchi is more than mere sustenance to the inhabitants of the region as it is both a way to divide the social world and an economic asset. Based on fieldwork in this region of rural Japan, this research examines how incorporated beliefs and pragmatic considerations participate in the social construction of taste for emblematic foods in Kōchi. On one hand, this research seeks to uncover how incorporated beliefs, values that are learnt, embodied, performed and transmitted, structure taste in the region. Habitus, culture and identity are some of the tools at our disposal to analyze how standards of taste are incorporated into people’s daily lives. Literally speaking, we taste the social world through the food we eat. On the other hand, this research investigates how pragmatic considerations and immediate concerns brought on by material conditions help fashion taste in Kōchi. In one of the poorest prefectures of Japan, the urgent need for revitalization makes the cuisine of the region a valuable resource for the residents of the region. Economic opportunities, government strategic planning and the forces of capitalism fuel the creation of new dishes and the promotion of traditional flavors. Thus, embedded representations that give meaning to food and regimes of values that ascribe worth to food shape residents palates. Finally, such an analysis needs to recognize that both taste preferences (i.e. the choices we make) and taste perceptions (i.e. how we experience flavor) are closely bound together. The social construction of taste is part of an integrated system that frames culinary choices as well as the sense of taste. A comprehensive model that combines complementary facets of what constitutes taste can further contribute to a better understanding of the contextual nature of deliciousness

Europeana communication bug: which intervention strategy for a better cooperation with creative industry?

Although Europeana as well as many GLAMs are very engaged - beside the main mission, i.e. spreading cultural heritage knowledge- in developing new strategies in order to make digital contents reusable for creative industry, these efforts have been successful just only in sporadic cases. A significant know how deficits in communication often compromises expected outcomes and impact. Indeed, what prevails is an idea of communication like an enhancement “instrument” intended on the one hand in purely economic (development) sense, on the other hand as a way for increasing and spreading knowledge. The main reference model is more or less as follows: digital objects are to be captured and/or transformed by digital technologies into sellable goods to put into circulation. Nevertheless, this approach risks neglecting the real nature of communication, and more in detail the one of digital heritage where it is strategic not so much producing objects and goods as taking part into sharing environments creation (media) by engaged communities, small or large they may be. The environments act as meeting and interchange point, and consequently as driving force of enhancing. Only in a complex context of network interaction on line accessible digital heritage contents become a strategic resource for creating environments in which their re/mediation can occur – provided that credible strategies exist, shared by stakeholders and users. This paper particularly describes a case study including proposals for an effective connection among Europeana, GLAMs and Creative Industry in the framework of Food and Drink digital heritage enhancement and promotion. Experimental experiences as the one described in this paper anyway confirm the relevance of up-to-date policies based on an adequate communication concept, on solid partnerships with enterprise and association networks, on collaborative on line environments, on effective availability at least for most of contents by increasing free licensing, and finally on grassroots content implementation involving prosumers audience, even if filtered by GLAMs

Deep learning in food category recognition

Integrating artificial intelligence with food category recognition has been a field of interest for research for the past few decades. It is potentially one of the next steps in revolutionizing human interaction with food. The modern advent of big data and the development of data-oriented fields like deep learning have provided advancements in food category recognition. With increasing computational power and ever-larger food datasets, the approach’s potential has yet to be realized. This survey provides an overview of methods that can be applied to various food category recognition tasks, including detecting type, ingredients, quality, and quantity. We survey the core components for constructing a machine learning system for food category recognition, including datasets, data augmentation, hand-crafted feature extraction, and machine learning algorithms. We place a particular focus on the field of deep learning, including the utilization of convolutional neural networks, transfer learning, and semi-supervised learning. We provide an overview of relevant studies to promote further developments in food category recognition for research and industrial applicationsMRC (MC_PC_17171)Royal Society (RP202G0230)BHF (AA/18/3/34220)Hope Foundation for Cancer Research (RM60G0680)GCRF (P202PF11)Sino-UK Industrial Fund (RP202G0289)LIAS (P202ED10Data Science Enhancement Fund (P202RE237)Fight for Sight (24NN201);Sino-UK Education Fund (OP202006)BBSRC (RM32G0178B8

Three Essays on the Role of Unstructured Data in Marketing Research

This thesis studies the use of firm and user-generated unstructured data (e.g., text and videos) for improving market research combining advances in text, audio and video processing with traditional economic modeling. The first chapter is joint work with K. Sudhir and Minkyung Kim. It addresses two significant challenges in using online text reviews to obtain fine-grained attribute level sentiment ratings. First, we develop a deep learning convolutional-LSTM hybrid model to account for language structure, in contrast to methods that rely on word frequency. The convolutional layer accounts for the spatial structure (adjacent word groups or phrases) and LSTM accounts for the sequential structure of language (sentiment distributed and modified across non-adjacent phrases). Second, we address the problem of missing attributes in text in constructing attribute sentiment scores---as reviewers write only about a subset of attributes and remain silent on others. We develop a model-based imputation strategy using a structural model of heterogeneous rating behavior. Using Yelp restaurant review data, we show superior accuracy in converting text to numerical attribute sentiment scores with our model. The structural model finds three reviewer segments with different motivations: status seeking, altruism/want voice, and need to vent/praise. Interestingly, our results show that reviewers write to inform and vent/praise, but not based on attribute importance. Our heterogeneous model-based imputation performs better than other common imputations; and importantly leads to managerially significant corrections in restaurant attribute ratings. The second essay, which is joint work with Aniko Oery and Joyee Deb is an information-theoretic model to study what causes selection in valence in user-generated reviews. The propensity of consumers to engage in word-of-mouth (WOM) differs after good versus bad experiences, which can result in positive or negative selection of user-generated reviews. We show how the strength of brand image (dispersion of consumer beliefs about quality) and the informativeness of good and bad experiences impacts selection of WOM in equilibrium. WOM is costly: Early adopters talk only if they can affect the receiver’s purchase. If the brand image is strong (consumer beliefs are homogeneous), only negative WOM can arise. With a weak brand image or heterogeneous beliefs, positive WOM can occur if positive experiences are sufficiently informative. Using data from Yelp.com, we show how strong brands (chain restaurants) systematically receive lower evaluations controlling for several restaurant and reviewer characteristics. The third essay which is joint work with K.Sudhir and Khai Chiong studies success factors of persuasive sales pitches from a multi-modal video dataset of buyer-seller interactions. A successful sales pitch is an outcome of both the content of the message as well as style of delivery. Moreover, unlike one-way interactions like speeches, sales pitches are a two-way process and hence interactivity as well as matching the wavelength of the buyer are also critical to the success of the pitch. We extract four groups of features: content-related, style-related, interactivity and similarity in order to build a predictive model of sales pitch effectiveness

The Influence of Transformational Leadership on Organization Performance

Purpose:  The objectives of this study were 1) to determine the direct effect of Transformational Leadership Competency (TLC) and Environment, Social, and Governance (ESG) affecting Balanced Scorecard (BSC), 2) to determine the indirect effect of TLC affecting BSC, and 3) to confirm the developed model of transformational of food industrial organization with public concern by confirming with P-value, RMSEA, GFI, AGFI, and Critical Number.   Theoretical framework:  This study focuses on the relationship between TLC and ESG to BSC that affects the efficiency and success of an organization.   Design/methodology/approach:  The quantitative approach with survey research was conducted to collect data from 150 Executive Officers (CEOs) of food business organizations in Thailand.   Findings:  The finding showed that TCL has a direct effect on ESG (p-value=0.001). TLC has a direct effect on BSC (p-value=0.001). ESG has a direct effect on BSC (p-value=0.001). TLC has an indirect effect on BSC (p-value=0.001).   Research, Practical & Social implications: The recommendation, TLC affected BSC with direct and indirect effects with 64.0 percent.  It implied that public concern is the essential intermediate variable that should be paid attention to introduce in the organization management in the current situation when TLC was integrated into modern management. However, to accomplish effective company management, ESG should be integrated into the transformation of organization management to meet the sustainable food industry.   Originality/value: The value of the study shows that TLC and ESG directly and indirectly influence BSC management and contribute to the organization performanc