This page has only limited features, please log in for full access.

Dr. George Caridakis
UoAegean / Athena RC

Basic Info

Basic Info is private.

Research Keywords & Expertise

0 Affective Computing
0 Artificial Intelligence
0 Human Computer Interaction
0 Cultural Informatics
0 Intelligent Interaction

Fingerprints

Human Computer Interaction
Affective Computing
Artificial Intelligence

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 18 August 2021 in Information
Reads 0
Downloads 0

As the amount of content that is created on social media is constantly increasing, more and more opinions and sentiments are expressed by people in various subjects. In this respect, sentiment analysis and opinion mining techniques can be valuable for the automatic analysis of huge textual corpora (comments, reviews, tweets etc.). Despite the advances in text mining algorithms, deep learning techniques, and text representation models, the results in such tasks are very good for only a few high-density languages (e.g., English) that possess large training corpora and rich linguistic resources; nevertheless, there is still room for improvement for the other lower-density languages as well. In this direction, the current work employs various language models for representing social media texts and text classifiers in the Greek language, for detecting the polarity of opinions expressed on social media. The experimental results on a related dataset collected by the authors of the current work are promising, since various classifiers based on the language models (naive bayesian, random forests, support vector machines, logistic regression, deep feed-forward neural networks) outperform those of word or sentence-based embeddings (word2vec, GloVe), achieving a classification accuracy of more than 80%. Additionally, a new language model for Greek social media has also been trained on the aforementioned dataset, proving that language models based on domain specific corpora can improve the performance of generic language models by a margin of 2%. Finally, the resulting models are made freely available to the research community.

ACS Style

Georgios Alexandridis; Iraklis Varlamis; Konstantinos Korovesis; George Caridakis; Panagiotis Tsantilas. A Survey on Sentiment Analysis and Opinion Mining in Greek Social Media. Information 2021, 12, 331 .

AMA Style

Georgios Alexandridis, Iraklis Varlamis, Konstantinos Korovesis, George Caridakis, Panagiotis Tsantilas. A Survey on Sentiment Analysis and Opinion Mining in Greek Social Media. Information. 2021; 12 (8):331.

Chicago/Turabian Style

Georgios Alexandridis; Iraklis Varlamis; Konstantinos Korovesis; George Caridakis; Panagiotis Tsantilas. 2021. "A Survey on Sentiment Analysis and Opinion Mining in Greek Social Media." Information 12, no. 8: 331.

Journal article
Published: 22 June 2021 in Applied Sciences
Reads 0
Downloads 0

The proliferation of smart things and the subsequent emergence of the Internet of Things has motivated the deployment of intelligent spaces that provide automated services to users. Context-awareness refers to the ability of the system to be aware of the virtual and physical environment, allowing more efficient personalization. Context modeling and reasoning are two important aspects of context-aware computing, since they enable the representation of contextual data and inference of high-level, meaningful information. Context-awareness middleware systems integrate context modeling and reasoning, providing abstraction and supporting heterogeneous context streams. In this work, such a context-awareness middleware system is presented, which integrates a proposed context model based on the adaptation and combination of the most prominent context categorization schemata. A hybrid reasoning procedure, which combines multiple techniques, is also proposed and integrated. The proposed system was evaluated in a real-case-scenario cultural space, which supports preventive conservation. The evaluation showed that the proposed system efficiently addressed both conceptual aspects, through means of representation and reasoning, and implementation aspects, through means of performance.

ACS Style

Konstantinos Michalakis; Yannis Christodoulou; George Caridakis; Yorghos Voutos; Phivos Mylonas. A Context-Aware Middleware for Context Modeling and Reasoning: A Case-Study in Smart Cultural Spaces. Applied Sciences 2021, 11, 5770 .

AMA Style

Konstantinos Michalakis, Yannis Christodoulou, George Caridakis, Yorghos Voutos, Phivos Mylonas. A Context-Aware Middleware for Context Modeling and Reasoning: A Case-Study in Smart Cultural Spaces. Applied Sciences. 2021; 11 (13):5770.

Chicago/Turabian Style

Konstantinos Michalakis; Yannis Christodoulou; George Caridakis; Yorghos Voutos; Phivos Mylonas. 2021. "A Context-Aware Middleware for Context Modeling and Reasoning: A Case-Study in Smart Cultural Spaces." Applied Sciences 11, no. 13: 5770.

Journal article
Published: 13 April 2021 in Sensors
Reads 0
Downloads 0

In this paper, a novel method to modify color images for the protanopia and deuteranopia color vision deficiencies is proposed. The method admits certain criteria, such as preserving image naturalness and color contrast enhancement. Four modules are employed in the process. First, fuzzy clustering-based color segmentation extracts key colors (which are the cluster centers) of the input image. Second, the key colors are mapped onto the CIE 1931 chromaticity diagram. Then, using the concept of confusion line (i.e., loci of colors confused by the color-blind), a sophisticated mechanism translates (i.e., removes) key colors lying on the same confusion line to different confusion lines so that they can be discriminated by the color-blind. In the third module, the key colors are further adapted by optimizing a regularized objective function that combines the aforementioned criteria. Fourth, the recolored image is obtained by color transfer that involves the adapted key colors and the associated fuzzy clusters. Three related methods are compared with the proposed one, using two performance indices, and evaluated by several experiments over 195 natural images and six digitized art paintings. The main outcomes of the comparative analysis are as follows. (a) Quantitative evaluation based on nonparametric statistical analysis is conducted by comparing the proposed method to each one of the other three methods for protanopia and deuteranopia, and for each index. In most of the comparisons, the Bonferroni adjusted p-values are <0.015, favoring the superiority of the proposed method. (b) Qualitative evaluation verifies the aesthetic appearance of the recolored images. (c) Subjective evaluation supports the above results.

ACS Style

George Tsekouras; Anastasios Rigos; Stamatis Chatzistamatis; John Tsimikas; Konstantinos Kotis; George Caridakis; Christos-Nikolaos Anagnostopoulos. A Novel Approach to Image Recoloring for Color Vision Deficiency. Sensors 2021, 21, 2740 .

AMA Style

George Tsekouras, Anastasios Rigos, Stamatis Chatzistamatis, John Tsimikas, Konstantinos Kotis, George Caridakis, Christos-Nikolaos Anagnostopoulos. A Novel Approach to Image Recoloring for Color Vision Deficiency. Sensors. 2021; 21 (8):2740.

Chicago/Turabian Style

George Tsekouras; Anastasios Rigos; Stamatis Chatzistamatis; John Tsimikas; Konstantinos Kotis; George Caridakis; Christos-Nikolaos Anagnostopoulos. 2021. "A Novel Approach to Image Recoloring for Color Vision Deficiency." Sensors 21, no. 8: 2740.

Journal article
Published: 04 June 2020 in Big Data and Cognitive Computing
Reads 0
Downloads 0

Recent developments in digital technologies regarding the cultural heritage domain have driven technological trends in comfortable and convenient traveling, by offering interactive and personalized user experiences. The emergence of big data analytics, recommendation systems and personalization techniques have created a smart research field, augmenting cultural heritage visitor’s experience. In this work, a novel, hybrid recommender system for cultural places is proposed, that combines user preference with cultural tourist typologies. Starting with the McKercher typology as a user classification research base, which extracts five categories of heritage tourists out of two variables (cultural centrality and depth of user experience) and using a questionnaire, an enriched cultural tourist typology is developed, where three additional variables governing cultural visitor types are also proposed (frequency of visits, visiting knowledge and duration of the visit). The extracted categories per user are fused in a robust collaborative filtering, matrix factorization-based recommendation algorithm as extra user features. The obtained results on reference data collected from eight cities exhibit an improvement in system performance, thereby indicating the robustness of the presented approach.

ACS Style

Markos Konstantakis; Georgios Alexandridis; George Caridakis. A Personalized Heritage-Oriented Recommender System Based on Extended Cultural Tourist Typologies. Big Data and Cognitive Computing 2020, 4, 12 .

AMA Style

Markos Konstantakis, Georgios Alexandridis, George Caridakis. A Personalized Heritage-Oriented Recommender System Based on Extended Cultural Tourist Typologies. Big Data and Cognitive Computing. 2020; 4 (2):12.

Chicago/Turabian Style

Markos Konstantakis; Georgios Alexandridis; George Caridakis. 2020. "A Personalized Heritage-Oriented Recommender System Based on Extended Cultural Tourist Typologies." Big Data and Cognitive Computing 4, no. 2: 12.

Conference paper
Published: 29 May 2020 in Collaboration in a Hyperconnected World
Reads 0
Downloads 0

Sentiment analysis is a vigorous research area, with many application domains. In this work, aspect-based sentiment prediction is examined as a component of a larger architecture that crawls, indexes and stores documents from a wide variety of online sources, including the most popular social networks. The textual part of the collected information is processed by a hybrid bi-directional long short-term memory architecture, coupled with convolutional layers along with an attention mechanism. The extracted textual features are then combined with other characteristics, such as the number of repetitions, the type and frequency of emoji ideograms in a fully-connected, feed-forward artificial neural network that performs the final prediction task. The obtained results, especially for the negative sentiment class, which is of particular importance in certain cases, are encouraging, underlying the robustness of the proposed approach.

ACS Style

Georgios Alexandridis; Konstantinos Michalakis; John Aliprantis; Pavlos Polydoras; Panagiotis Tsantilas; George Caridakis. A Deep Learning Approach to Aspect-Based Sentiment Prediction. Collaboration in a Hyperconnected World 2020, 397 -408.

AMA Style

Georgios Alexandridis, Konstantinos Michalakis, John Aliprantis, Pavlos Polydoras, Panagiotis Tsantilas, George Caridakis. A Deep Learning Approach to Aspect-Based Sentiment Prediction. Collaboration in a Hyperconnected World. 2020; ():397-408.

Chicago/Turabian Style

Georgios Alexandridis; Konstantinos Michalakis; John Aliprantis; Pavlos Polydoras; Panagiotis Tsantilas; George Caridakis. 2020. "A Deep Learning Approach to Aspect-Based Sentiment Prediction." Collaboration in a Hyperconnected World , no. : 397-408.

Journal article
Published: 04 March 2020 in Algorithms
Reads 0
Downloads 0

Short-term property rentals are perhaps one of the most common traits of present day shared economy. Moreover, they are acknowledged as a major driving force behind changes in urban landscapes, ranging from established metropolises to developing townships, as well as a facilitator of geographical mobility. A geolocation ontology is a high level inference tool, typically represented as a labeled graph, for discovering latent patterns from a plethora of unstructured and multimodal data. In this work, a two-step methodological framework is proposed, where the results of various geolocation analyses, important in their own respect, such as ghost hotel discovery, form intermediate building blocks towards an enriched knowledge graph. The outlined methodology is validated upon data crawled from the Airbnb website and more specifically, on keywords extracted from comments made by users of the said platform. A rather solid case-study, based on the aforementioned type of data regarding Athens, Greece, is addressed in detail, studying the different degrees of expansion & prevalence of the phenomenon among the city’s various neighborhoods.

ACS Style

Georgios Alexandridis; Yorghos Voutos; Phivos Mylonas; George Caridakis. A Geolocation Analytics-Driven Ontology for Short-Term Leases: Inferring Current Sharing Economy Trends. Algorithms 2020, 13, 59 .

AMA Style

Georgios Alexandridis, Yorghos Voutos, Phivos Mylonas, George Caridakis. A Geolocation Analytics-Driven Ontology for Short-Term Leases: Inferring Current Sharing Economy Trends. Algorithms. 2020; 13 (3):59.

Chicago/Turabian Style

Georgios Alexandridis; Yorghos Voutos; Phivos Mylonas; George Caridakis. 2020. "A Geolocation Analytics-Driven Ontology for Short-Term Leases: Inferring Current Sharing Economy Trends." Algorithms 13, no. 3: 59.

Conference paper
Published: 01 November 2019 in Transactions on Petri Nets and Other Models of Concurrency XV
Reads 0
Downloads 0

The main feature of a Serious Game (SG) is its objective of supporting the player to achieve learning targets through a fun experience. The paper focuses on the creation of a digital cultural SG, named “The stolen painting”. The main goal of this game is to initiate users into art painting, through game activities that encourage the users to learn about some of the most famous paintings in the world and their creators. The theory of Gardner’s Multiple Intelligences (MI) is used for game profile identification through social media data mining techniques, or alternatively, through Multiple Intelligences Profiling Questionnaire (MIPQ) in order to reveal and quantify the different types of intellectual strengths (intelligences) that each user exhibits. Game’s progress is based on the three strongest intelligences of the player and the main objective of the player is to reveal the stolen painting’s identity.

ACS Style

Markos Konstantakis; Eirini Kalatha; George Caridakis. Cultural Heritage, Serious Games and User Personas Based on Gardner’s Theory of Multiple Intelligences: “The Stolen Painting” Game. Transactions on Petri Nets and Other Models of Concurrency XV 2019, 490 -500.

AMA Style

Markos Konstantakis, Eirini Kalatha, George Caridakis. Cultural Heritage, Serious Games and User Personas Based on Gardner’s Theory of Multiple Intelligences: “The Stolen Painting” Game. Transactions on Petri Nets and Other Models of Concurrency XV. 2019; ():490-500.

Chicago/Turabian Style

Markos Konstantakis; Eirini Kalatha; George Caridakis. 2019. "Cultural Heritage, Serious Games and User Personas Based on Gardner’s Theory of Multiple Intelligences: “The Stolen Painting” Game." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 490-500.

Conference paper
Published: 15 May 2019 in IFIP Advances in Information and Communication Technology
Reads 0
Downloads 0

This work constitutes a theoretically-informed empirical analysis of the spatial characteristics of the short-term rentals’ market and explores their linkage with shifts in the wider housing market within the context of a south-eastern EU metropolis. The same research objective has been pursued for a variety of international paradigms; however, to the best of our knowledge, there has not been a thorough and systematic study for Athens and its neighborhoods. With a theoretical framework that draws insight from the political-economic views of Critical Geography, this work departs from an assessment of Airbnb listings, and proceeds inquiring the expansion of the phenomenon with respect to the rates of long-term rent levels in the neighborhoods of Central Athens, utilizing relevant data. The geographical framework covers the City of Athens as a whole, an area undergoing profound transformations in recent years, stemming from diverse factors that render the city one of the most dynamic destinations of urban tourism and speculative land investment. The analysis reveals a prominent expansion of the short-term rental phenomenon across the urban fabric, especially taking ground in hitherto underexploited areas. This expansion is multifactorial, asynchronous and exhibits signs of positive relation with the long-term rentals shifts; Airbnb not only affects already gentrifying neighborhoods, but contributes to a housing market disruption in non-dynamic residential areas.

ACS Style

Konstantinos Gourzis; Georgios Alexandridis; Stelios Gialis; George Caridakis. Studying the Spatialities of Short-Term Rentals’ Sprawl in the Urban Fabric: The Case of Airbnb in Athens, Greece. IFIP Advances in Information and Communication Technology 2019, 196 -207.

AMA Style

Konstantinos Gourzis, Georgios Alexandridis, Stelios Gialis, George Caridakis. Studying the Spatialities of Short-Term Rentals’ Sprawl in the Urban Fabric: The Case of Airbnb in Athens, Greece. IFIP Advances in Information and Communication Technology. 2019; ():196-207.

Chicago/Turabian Style

Konstantinos Gourzis; Georgios Alexandridis; Stelios Gialis; George Caridakis. 2019. "Studying the Spatialities of Short-Term Rentals’ Sprawl in the Urban Fabric: The Case of Airbnb in Athens, Greece." IFIP Advances in Information and Communication Technology , no. : 196-207.

Article
Published: 13 February 2019 in User Modeling and User-Adapted Interaction
Reads 0
Downloads 0

Although abundant research work has been published in the area of path recommendation and its applications on travel and routing topics, scarce work has been reported on context-aware route recommendation systems aimed to stimulate optimal cultural heritage experiences. This paper tries to address this issue, by proposing a personalized and content adaptive cultural heritage path recommendation system, where location is modeled using mean-shift clustering trained with actual user movement patters. Additionally, topic modeling is incorporated to formalize the implicit cultural heritage content, while first order Markov models address the movement as a temporal transition aspect of the problem. The overall architecture is applied on data collected from actual visits to the archaeological sites of Gournia and Çatalhöyük and extensive analysis on visitor movement patterns follows, especially in comparison to the curated paths in the aforementioned sites. Finally, the offline evaluation results of the proposed recommendation scheme are encouraging, validating its efficiency and setting a positive paradigm for cultural heritage route recommendations.

ACS Style

Georgios Alexandridis; Angeliki Chrysanthi; George E. Tsekouras; George Caridakis. Personalized and content adaptive cultural heritage path recommendation: an application to the Gournia and Çatalhöyük archaeological sites. User Modeling and User-Adapted Interaction 2019, 29, 201 -238.

AMA Style

Georgios Alexandridis, Angeliki Chrysanthi, George E. Tsekouras, George Caridakis. Personalized and content adaptive cultural heritage path recommendation: an application to the Gournia and Çatalhöyük archaeological sites. User Modeling and User-Adapted Interaction. 2019; 29 (1):201-238.

Chicago/Turabian Style

Georgios Alexandridis; Angeliki Chrysanthi; George E. Tsekouras; George Caridakis. 2019. "Personalized and content adaptive cultural heritage path recommendation: an application to the Gournia and Çatalhöyük archaeological sites." User Modeling and User-Adapted Interaction 29, no. 1: 201-238.

Review
Published: 12 February 2019 in Heritage
Reads 0
Downloads 0

The Cultural Heritage (CH) domain encompasses a wide range of different disciplines, serving the study, interpretation, curation, and preservation of objects, collections, archives, sites, and the dissemination of related knowledge. In this context, stakeholders generate, retrieve, and share a vast amount of diverse information. Therefore, information interoperability has been considered a crucial task, especially in terms of semantics. In this way, the CIDOC CRM (International Committee for Documentation Conceptual Reference Model) has been widely used as an underlying model that offers interoperability between CH domain metadata standards and ontologies. To the best of our knowledge, an overall review of mapping, merging, and extending this core ontology, as well as an aggregate table which classifies and correlates those ontologies and standards, has not yet been presented. Our study conducts an aggregate review of relevant published efforts and outlines the various associations between them, encapsulating the CIDOC CRM and its specialized models, as well. This work aims to further clarify the field and scope of the different works, identify their methods, and highlight the semantic overlap, or differences, between them.

ACS Style

Efthymia Moraitou; John Aliprantis; Yannis Christodoulou; Alexandros Teneketzis; George Caridakis. Semantic Bridging of Cultural Heritage Disciplines and Tasks. Heritage 2019, 2, 611 -630.

AMA Style

Efthymia Moraitou, John Aliprantis, Yannis Christodoulou, Alexandros Teneketzis, George Caridakis. Semantic Bridging of Cultural Heritage Disciplines and Tasks. Heritage. 2019; 2 (1):611-630.

Chicago/Turabian Style

Efthymia Moraitou; John Aliprantis; Yannis Christodoulou; Alexandros Teneketzis; George Caridakis. 2019. "Semantic Bridging of Cultural Heritage Disciplines and Tasks." Heritage 2, no. 1: 611-630.

Journal article
Published: 22 October 2018 in Algorithms
Reads 0
Downloads 0

The ability to learn robust, resizable feature representations from unlabeled data has potential applications in a wide variety of machine learning tasks. One way to create such representations is to train deep generative models that can learn to capture the complex distribution of real-world data. Generative adversarial network (GAN) approaches have shown impressive results in producing generative models of images, but relatively little work has been done on evaluating the performance of these methods for the learning representation of natural language, both in supervised and unsupervised settings at the document, sentence, and aspect level. Extensive research validation experiments were performed by leveraging the 20 Newsgroups corpus, the Movie Review (MR) Dataset, and the Finegrained Sentiment Dataset (FSD). Our experimental analysis suggests that GANs can successfully learn representations of natural language texts at all three aforementioned levels.

ACS Style

Aggeliki Vlachostergiou; George Caridakis; Phivos Mylonas; Andreas Stafylopatis. Learning Representations of Natural Language Texts with Generative Adversarial Networks at Document, Sentence, and Aspect Level. Algorithms 2018, 11, 164 .

AMA Style

Aggeliki Vlachostergiou, George Caridakis, Phivos Mylonas, Andreas Stafylopatis. Learning Representations of Natural Language Texts with Generative Adversarial Networks at Document, Sentence, and Aspect Level. Algorithms. 2018; 11 (10):164.

Chicago/Turabian Style

Aggeliki Vlachostergiou; George Caridakis; Phivos Mylonas; Andreas Stafylopatis. 2018. "Learning Representations of Natural Language Texts with Generative Adversarial Networks at Document, Sentence, and Aspect Level." Algorithms 11, no. 10: 164.

Journal article
Published: 01 May 2016 in Engineering Applications of Artificial Intelligence
Reads 0
Downloads 0

Affective computing researchers adopt a variety of methods in analysing or synthesizing aspects of human behaviour. The choice of method depends on which behavioural cues are considered salient or straightforward to capture and comprehend, as well as the overall context of the interaction. Thus, each approach focuses on modelling certain information and results to dedicated representations. However, analysis or synthesis is usually done by following label-based representations, which usually have a direct mapping to a feature vector. The goal of the presented work is to introduce an interim representational mechanism that associates low-level gesture expressivity parameters with a high-level dimensional representation of affect. More specifically, it introduces a novel methodology for associating easily extracted, low-level gesture data to the affective dimensions of activation and evaluation. For this purpose, a user perception test was carried out in order to properly annotate a dataset, by asking participants to assess each gesture in terms of the perceived activation (active/passive) and evaluation (positive/negative) levels. In affective behaviour modelling, the contribution of the proposed association methodology is twofold: On one hand, when analysing affective behaviour, it can enable the fusion of expressivity parameters alongside with any other modalities coded in higher-level affective representations, leading, in this way, to scalable multimodal analysis. On the other hand, it can enforce the process of synthesizing composite human behaviour (e.g. facial expression, gestures and body posture) since it allows for the translation of dimensional values of affect into synthesized expressive gestures.

ACS Style

Lori Malatesta; Stylianos Asteriadis; George Caridakis; Asimina Vasalou; Kostas Karpouzis. Associating gesture expressivity with affective representations. Engineering Applications of Artificial Intelligence 2016, 51, 124 -135.

AMA Style

Lori Malatesta, Stylianos Asteriadis, George Caridakis, Asimina Vasalou, Kostas Karpouzis. Associating gesture expressivity with affective representations. Engineering Applications of Artificial Intelligence. 2016; 51 ():124-135.

Chicago/Turabian Style

Lori Malatesta; Stylianos Asteriadis; George Caridakis; Asimina Vasalou; Kostas Karpouzis. 2016. "Associating gesture expressivity with affective representations." Engineering Applications of Artificial Intelligence 51, no. : 124-135.

Conference paper
Published: 01 November 2015 in 2015 10th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)
Reads 0
Downloads 0

EU FIRE research project "Social and Smart" aims to formalize and build a complete ecosystem of users, context sensors and smart home appliances that interact following the ubiquitous computing paradigm in order to adapt and enhance the everyday user-appliance interaction. In this framework a user is modeled through the use of Personas stereotypes. Contextual information is collected via wireless ambient sensors, such as temperature and humidity ones, but can also include Smart City sensors and services. This contextual information is further re-lated to each user's model through the enforcement of home rules, expressed in a high level language. Knowledge representation is supported through Semantic Web technologies that also ensure the interoperability between all the actors of the ecosystem. Preliminary experimental results have been carried in a small scale Smart Home setting, but also in a larger scale using the FIWARE1 framework provided by the SmartSandander testbed.

ACS Style

Georgios Stratogiannis; Aggeliki Vlachostergiou; Georgios Siolas; George Caridakis; Phivos Mylonas; Andreas Stafylopatis; Stefanos Kollias. User and home appliances pervasive interaction in a sensor driven smart home environment: The SandS approach. 2015 10th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) 2015, 1 -6.

AMA Style

Georgios Stratogiannis, Aggeliki Vlachostergiou, Georgios Siolas, George Caridakis, Phivos Mylonas, Andreas Stafylopatis, Stefanos Kollias. User and home appliances pervasive interaction in a sensor driven smart home environment: The SandS approach. 2015 10th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP). 2015; ():1-6.

Chicago/Turabian Style

Georgios Stratogiannis; Aggeliki Vlachostergiou; Georgios Siolas; George Caridakis; Phivos Mylonas; Andreas Stafylopatis; Stefanos Kollias. 2015. "User and home appliances pervasive interaction in a sensor driven smart home environment: The SandS approach." 2015 10th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) , no. : 1-6.

Conference paper
Published: 21 July 2015 in Transactions on Petri Nets and Other Models of Concurrency XV
Reads 0
Downloads 0

The ability of humans to effectively interact socially relies heavily on their awareness of the context the interaction takes place. In order for computer systems to accordingly possess the same ability, it is crucial they are also context-aware in terms of a formalization of context based on the W5+ framework aspects of Who, What, Why, Where, What and How. Research work presented in this paper contributes towards this goal by bridging the conceptual gap and exploiting semantics and cognitive and affective information of non verbal behavior and investigating whether and how this information could be incorporated in automatic analysis of affective behavior. A semantic concept extraction methodology is proposed and its application to indicative examples from the SEMAINE corpus is presented that validates the proposed approach.

ACS Style

Aggeliki Vlachostergiou; George Caridakis; Amaryllis Raouzaiou; Stefanos Kollias. HCI and Natural Progression of Context-Related Questions. Transactions on Petri Nets and Other Models of Concurrency XV 2015, 530 -541.

AMA Style

Aggeliki Vlachostergiou, George Caridakis, Amaryllis Raouzaiou, Stefanos Kollias. HCI and Natural Progression of Context-Related Questions. Transactions on Petri Nets and Other Models of Concurrency XV. 2015; ():530-541.

Chicago/Turabian Style

Aggeliki Vlachostergiou; George Caridakis; Amaryllis Raouzaiou; Stefanos Kollias. 2015. "HCI and Natural Progression of Context-Related Questions." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 530-541.

Journal article
Published: 01 July 2015 in International Journal of Virtual Communities and Social Networking
Reads 0
Downloads 0

The current paper provides an overview on how user modeling, context awareness and content adaptation in Smart Home environments may be handled formally in order to capture the semantics that emerge from a newly introduced user experience: SandS is in fact a complete ecosystem of users within a social network, creating and exchanging content in the form of so-called recipes and developing a collective intelligence which adapts its operation through appropriate feedback provided by the user. The authors will approach SandS from the user's perspective and illustrate how users and their relationships can be modeled through a number of fuzzy stereotypical profiles. Additionally, context modeling in pervasive computing systems and especially in the Smart Home paradigm will be examined through appropriate representation of context cues in the overall interaction. Finally, the authors will investigate how users and system services although using languages of different semantic expressiveness can inter-operate successfully thanks to appropriate knowledge-based expert mappings.

ACS Style

Giorgos Siolas; George Caridakis; Phivos Mylonas; Giorgos Stratogiannis; Stefanos Kollias; Andreas Stafylopatis. Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments. International Journal of Virtual Communities and Social Networking 2015, 7, 17 -50.

AMA Style

Giorgos Siolas, George Caridakis, Phivos Mylonas, Giorgos Stratogiannis, Stefanos Kollias, Andreas Stafylopatis. Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments. International Journal of Virtual Communities and Social Networking. 2015; 7 (3):17-50.

Chicago/Turabian Style

Giorgos Siolas; George Caridakis; Phivos Mylonas; Giorgos Stratogiannis; Stefanos Kollias; Andreas Stafylopatis. 2015. "Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments." International Journal of Virtual Communities and Social Networking 7, no. 3: 17-50.

Book chapter
Published: 18 June 2014 in Dermoscopy Image Analysis
Reads 0
Downloads 0
ACS Style

Charline Hondrou; George Caridakis; Kostas Karpouzis; Stefanos Kollias. Affective Natural Interaction Using EEG: Technologies, Applications, and Future Directions. Dermoscopy Image Analysis 2014, 397 -419.

AMA Style

Charline Hondrou, George Caridakis, Kostas Karpouzis, Stefanos Kollias. Affective Natural Interaction Using EEG: Technologies, Applications, and Future Directions. Dermoscopy Image Analysis. 2014; ():397-419.

Chicago/Turabian Style

Charline Hondrou; George Caridakis; Kostas Karpouzis; Stefanos Kollias. 2014. "Affective Natural Interaction Using EEG: Technologies, Applications, and Future Directions." Dermoscopy Image Analysis , no. : 397-419.

Journal article
Published: 01 January 2014 in Procedia Computer Science
Reads 0
Downloads 0
ACS Style

Aggeliki Vlachostergiou; George Caridakis; Stefanos Kollias. Investigating Context Awareness of Affective Computing Systems: A Critical Approach. Procedia Computer Science 2014, 39, 91 -98.

AMA Style

Aggeliki Vlachostergiou, George Caridakis, Stefanos Kollias. Investigating Context Awareness of Affective Computing Systems: A Critical Approach. Procedia Computer Science. 2014; 39 ():91-98.

Chicago/Turabian Style

Aggeliki Vlachostergiou; George Caridakis; Stefanos Kollias. 2014. "Investigating Context Awareness of Affective Computing Systems: A Critical Approach." Procedia Computer Science 39, no. : 91-98.

Conference paper
Published: 01 December 2013 in 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization
Reads 0
Downloads 0

Current paper investigates how user modeling, context awareness and content adaptation in Smart Home environments can be handled formally in order to capture the semantics that emerge from a newly introduced user experience: SandS is in fact a complete ecosystem of users within a social network, creating and exchanging content in the form of so-called recipes and developing a collective intelligence which adapts its operation through appropriately feedback provided by the user. We will approach SandS from the user's perspective and illustrate how users and their relationships can be modeled through a number of fuzzy stereotypical profiles. Additionally, context modeling in pervasive computing systems and especially in the Smart Home paradigm will be examined through appropriate representation of context cues in the overall interaction. Finally we will investigate how users and system services although using languages of different semantic expressiveness can inter-operate successfully thanks to appropriate knowledge-based expert mappings.

ACS Style

Giorgos Siolas; George Caridakis; Phivos Mylonas; Stefanos Kollias; Andreas Stafylopatis; Georgios Siolas; Spyridon Kollias. Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments. 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization 2013, 27 -32.

AMA Style

Giorgos Siolas, George Caridakis, Phivos Mylonas, Stefanos Kollias, Andreas Stafylopatis, Georgios Siolas, Spyridon Kollias. Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments. 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization. 2013; ():27-32.

Chicago/Turabian Style

Giorgos Siolas; George Caridakis; Phivos Mylonas; Stefanos Kollias; Andreas Stafylopatis; Georgios Siolas; Spyridon Kollias. 2013. "Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments." 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization , no. : 27-32.

Journal article
Published: 26 April 2013 in Journal on Multimodal User Interfaces
Reads 0
Downloads 0

Recording and annotating a multimodal database of natural expressivity is a task that requires careful planning and implementation, before even starting to apply feature extraction and recognition algorithms. Requirements and characteristics of such databases are inherently different than those of acted behaviour, both in terms of unconstrained expressivity of the human participants, and in terms of the expressed emotions. In this paper, we describe a method to induce, record and annotate natural emotions, which was used to provide multimodal data for dynamic emotion recognition from facial expressions and speech prosody; results from a dynamic recognition algorithm, based on recurrent neural networks, indicate that multimodal processing surpasses both speech and visual analysis by a wide margin. The SAL database was used in the framework of the Humaine Network of Excellence as a common ground for research in everyday, natural emotions.

ACS Style

Kostas Karpouzis; George Caridakis; Roddy Cowie; Ellen Douglas-Cowie. Induction, recording and recognition of natural emotions from facial expressions and speech prosody. Journal on Multimodal User Interfaces 2013, 7, 195 -206.

AMA Style

Kostas Karpouzis, George Caridakis, Roddy Cowie, Ellen Douglas-Cowie. Induction, recording and recognition of natural emotions from facial expressions and speech prosody. Journal on Multimodal User Interfaces. 2013; 7 (3):195-206.

Chicago/Turabian Style

Kostas Karpouzis; George Caridakis; Roddy Cowie; Ellen Douglas-Cowie. 2013. "Induction, recording and recognition of natural emotions from facial expressions and speech prosody." Journal on Multimodal User Interfaces 7, no. 3: 195-206.

Comparative study
Published: 01 December 2012 in Neural Networks
Reads 0
Downloads 0

Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost

ACS Style

G. Caridakis; K. Karpouzis; A. Drosopoulos; S. Kollias. Non parametric, self organizing, scalable modeling of spatiotemporal inputs: The sign language paradigm. Neural Networks 2012, 36, 157 -166.

AMA Style

G. Caridakis, K. Karpouzis, A. Drosopoulos, S. Kollias. Non parametric, self organizing, scalable modeling of spatiotemporal inputs: The sign language paradigm. Neural Networks. 2012; 36 ():157-166.

Chicago/Turabian Style

G. Caridakis; K. Karpouzis; A. Drosopoulos; S. Kollias. 2012. "Non parametric, self organizing, scalable modeling of spatiotemporal inputs: The sign language paradigm." Neural Networks 36, no. : 157-166.