Ioannis Kopanakis

Hellenic Mediterranean University · Department of Management Science and Technology (Agios Nikolaos)

It is estimated that European households are responsible for 55% of food waste generation. Key factors contributing to household food waste generation include food spoilage, confusion over expiration dates, overbuying, and inadequate shopping planning. Thus, food waste prevention at the household level depends heavily on food supplies monitoring an...

The COVID-19 pandemic has heavily affected the global travel and tourism industries. Closed borders, reduction of flights, strict travel restrictions, lockdown measures, social distancing, have resulted in a reluctance of tourists to travel, and led to a huge drop in tourist flows. In this context, the aim of this chapter is to investigate the chan...

In Europe, it is estimated that households are responsible for the largest portion of food waste generation, which contributes up to 16% of the CO2 emissions of the food supply chain. Major reasons for household food waste generation are food spoilage, date label confusion, overbuying, and poor shopping planning (Gunders, 2017). Thus, food-waste pr...

Nowadays, local authorities and tourism enterprises are using conventional methods like surveys and opinion polls for collecting data and strategic decision making. Despite the benefits of these approaches, they present significant disadvantages such as time-consuming and sample size. This research paper investigates the user-generated data in Loca...

Digital marketers have a range of tools at their disposal for understanding customers and prospects on social media. These tools allow for better social media monitoring and analysis through the provision of vital insights. The use of artificial intelligence (AI) to such analysis enables for marketing tasks automation, accuracy improvement and huma...

Social media networks are a resource for valuable knowledge about tourist destinations through the collection of data by Location-Based Social Networks (LBSN). A major problem is the lack of knowledge in respect to the visitors’ views about a destination, as well as the fact that the visitors’ behavior needs and preferences are not visible. Many en...

In the era of the fourth industrial revolution (Industry 4.0), big data has major impact on businesses, since the revolution of networks, platforms, people and digital technology have changed the determinants of firms’ innovation and competitiveness. An ongoing huge hype for big data has been gained from academics and professionals, since big data...

Destination Marketing Organizations (DMOs) have to redefine their marketing strategies, in order to meet current challenges in tourism, such as the emergence of new tourism destinations, the intense competition, the change in the motivations and preferences of tourists, as well as the global economic crisis. On the other hand, social media are gain...

In the era of Industry 4.0 (4th industrial revolution), data has major impact on businesses, since the revolution of networks, platforms, people and digital technology changed the determinants of firms' innovation and competitiveness (OECD, 2015). In the ―knowledge-based economy‖, enterprises have to be innovative in order to build and sustain a co...

In the "knowledge-based economy", enterprises have to be innovative in order to build and sustain a competitive advantage against rivals. However, innovation is complex due to fast changing technology, globalization (extremely competitive market conditions) and changing customers' needs. As innovation is dependent on the combination of technologies...

The emergence of the 5th generation wireless standard for telecommunications (5G) will enable the Internet of Things (IoT), a huge network of interconnected devices that can be utilized in almost every aspect of our daily lives, either that is in healthcare, transportation, environmental monitoring, and so on. As good as it sounds though, individua...

The preservation of privacy when publishing spatiotemporal traces of mobile humans is a field that is receiving growing attention. However, while more and more services offer personalized privacy options to their users, few trajectory anonymization algorithms are able to handle personalization effectively, without incurring unnecessary information...

This chapter elaborates on energy usage optimization issues by exploiting a resource offloading process based on a social-oriented mobile cloud scheme. The adoption of the proposed scheme enables for increasing the reliability in services provision to the mobile users by guaranteeing sufficient resources for the mobile application execution. More s...

This article proposes a novel model to optimize e-marketing planning in tourism sector, based on the convergence among interactive digital television, mobile networks and cloud computing systems. The proposed research approach is exploited, towards efficiently facilitating marketers to accomplish optimum e-marketing data analysis and design effecti...

This article proposes a novel model to optimize e-marketing planning in tourism sector, based on the convergence among interactive digital television, mobile networks and cloud computing systems. The proposed research approach is exploited, towards efficiently facilitating marketers to accomplish optimum e-marketing data analysis and design effecti...

This paper proposes a novel electronic customer relationship management (e-CRM) model based on the convergence among interactive digital television and multimedia networks. This model enables for the design of effective advertising strategies in tourism industry, by exploiting data mining methods such as predictive visual analytics. The e-marketing...

This paper proposes an efficient customer relationship management model based on technological convergence of emerging next generation networks, such as interactive digital television and network multimedia systems. The proposed research approach is exploited in tourism sector for effective destination management, enabling for personalized e-market...

This paper proposes an efficient customer relationship management model based on technological convergence of emerging next generation networks, such as interactive digital television and network multimedia systems. The proposed research approach is exploited in tourism sector for effective destination management, enabling for personalized e-market...

This paper proposes an efficient customer relationship management framework/model based on technological convergence of emerging next generation networks, such as interactive digital television and network multimedia systems. The proposed research approach is exploited in tourism and hospitality sector for effective destination management, enabling...

Current trends in global tourism including the emergence of new tourism destinations, the intense competition, the change in the motivations and preferences of tourists, as well as the continuing economic crisis have forced tourism destinations to seek more innovative marketing strategies, towards achieving a competitive advantage. Destination Mark...

This paper proposes a technology interactivity model that enables the convergence of digital television with network multimedia systems. The proposed research approach is exploited in tourism relationship marketing, providing an efficient mechanism that facilitates marketers to accomplish optimum analysis of marketing data. Results of this analysis...

This paper investigates the convergence of network multimedia and interactive digital television systems and elaborates on a novel research approach that may be adopted in tourism relationship marketing, towards enabling for an efficient process of collecting and analyzing feedback data from tele-viewers. This process may be vital for optimum marke...

Social media are gaining prominence as an effective tool for destination marketing. Used properly, social media provides destination management organizations (DMOs) with a low cost but very effective global marketing, communications and customer engagement platform. In fact, social media pose both opportunities and challenges for DMOs. In this resp...

Interactive broadcasting elaborates on the investigation and realization of novel digital television networks, able to provide multiple interactive multimedia and Internet based services, utilizing Digital Video Broadcasting (DVB) advances. On the other hand, IP Multimedia Subsystem (IMS) is a promising solution that may be adopted in next generati...

Interactive broadcasting elaborates on the study and realization of novel television networks, able to provide multiple interactive multimedia and Internet based services, utilizing Digital Video Broadcasting advances. On the other hand, IP Multimedia Subsystem (IMS) is a promising solution, that may be adopted in next generation networks and broad...

In this paper we describe our approach to discover trends for the biotechnology and pharmaceutical industry based on temporal text mining. Temporal text mining combines information extraction and data mining techniques upon textual repositories and our main objective is to identify changes of associations among entities of interest over time. It co...

Data analysis and knowledge discovery over moving object databases discovers behavioral patterns of moving objects that can be exploited in applications like traffic management and location-based services. Similarity search over trajectories is imperative for supporting such tasks. Related works in the field, mainly inspired from the time-series do...

Moving Object Databases (MOD), although ubiquitous, still call for methods that will be able to understand, search, analyze, and browse their spatiotemporal content. In this paper, we propose a method for trajectory segmentation and sampling based on the representativeness of the (sub-)trajectories in the MOD. In order to find the most representati...

A novel methodology for efficiently sampling Trajectory Databases (TD) for mobility data mining purposes is presented. In particular, a three-step unsupervised trajectory sampling methodology is proposed, that initially adopts a symbolic vector representation of a trajectory which, using a similarity-based voting technique, is transformed to aconti...

Knowledge discovery in Trajectory Databases (TD) is an emerging field which has recently gained great interest. On the otherhand, the inherent presence of uncertainty in TD (e.g., due to GPS errors) has not been taken yet into account during the mining process. In this paper, we study the effect of uncertainty in TD clustering and introduce a three...

Mining Trajectory Databases (TD) has recently gained great interest due to the popularity of tracking devices. On the other hand, the inherent presence of uncertainty in TD (e.g., due to GPS errors) has not been taken yet into account during the mining process. In this paper1, we study the effect of uncertainty in TD clustering and introduce a thre...

We propose a method for trajectory classification based on trajectory voting in Moving Object Databases (MOD). Trajectory voting is performed based on local trajectory similarity. This is a relatively new topic in the spatial and spatiotemporal database literature with a variety of applications like trajectory summarization, classification, searchi...

In this paper we describe an application of our approach to temporal text mining in Competitive Intelligence for the biotechnology and pharmaceutical industry. The main objective is to identify changes and trends of associations among entities of interest that appear in text over time. Text Mining (TM) exploits information contained in textual data...

On our attempt to handle adequately the age of the data glut, exploring and analyzing the vast volumes of data is becoming increasingly challenging, as never before in history has data been generated at such high volumes as it is today. In the context of geo-spatial data, large spatial data sets occur naturally when accumulating many samples or rea...

In this paper, we propose a novel scheme for efficient content-based medical image retrieval, formalized according to the PAtterns for Next generation DAtabase systems (PANDA) framework for pattern representation and management. The proposed scheme involves block-based low-level feature extraction from images followed by the clustering of the featu...

Intuitionistic fuzzy sets are generalized fuzzy sets whose elements are characterized by a membership, as well as a non-membership value. The membership value indicates the degree of belongingness, whereas the non-membership value indicates the degree of non-belongingness of an element to that set. The utility of intuitionistic fuzzy sets theory in...

In this paper we present an overview of the MetaOn system. The core target of MetaOn is to construct and integrate semantically rich metadata extracted from documents, images and linguistic resources, to facilitate intelligent search and analysis. The MetaOn framework involves ontology-based information extraction and data mining, semi-automatic co...

Clustering approaches organize a set of objects into groups whose members are proximate according to some similarity function defined on low- level features, assuming that their values are not subject to any kind of uncertainty. Furthermore, these methods assume that similarity is measured by accounting only the degree in which two entities are rel...

Content-based information retrieval (IR) involves low-level feature extraction and utilize similarity search methods applied either in the feature space or in derived higher-level semantic spaces. These methods assume that similarity is measured by accounting only the degree in which two entities are related, ignoring the hesitancy introduced by th...

We study the problem of classification as this is presented in the context of data mining. Among the various approaches that are investigated, we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical...

All the power of computational techniques for data processing and analysis is worthless without human analysts choosing appropriate methods depending on data characteristics, setting parameters and controlling the work of the methods, interpreting results obtained, understanding what to do next, reasoning, and drawing conclusions. To enable effecti...

Trajectory database (TD) management is a relatively new topic of database research, which has emerged due to the explosion of mobile devices and positioning technologies. Trajectory similarity search forms an important class of queries in TD with applications in trajectory data analysis and spatiotemporal knowledge discovery. In contrast to related...

With the rapid progress of mobile devices and positioning technologies, Trajectory databases (TD) have been in the core of database research during the last decade. Analysis and knowledge discovery in TD is an emerging field which has recently gained great interest. Extracting knowledge from TD using certain types of mining techniques, such as clus...

Conventional Content-Based Image Retrieval (CBIR) systems make use of similarity measures estimated directly from low-level image features, involving multidimensional and exhaustive, nearest neighbor searching. In this paper we present an image retrieval methodology suited for efficient search in cultural heritage images that utilizes similarity me...

State of the art in multimedia technology focuses in managing data collected from various sources, including documents, images, video, and speech. Therefore the effective management, analysis and mining of such heterogeneous data require the combination of various techniques. In this paper, we present an overview of the funded MetaOn project. The c...

In this paper we present an overview of the intelligent multimedia annotation and search system MetaOn. The core objective is to construct and integrate semantically rich metadata, extracted from documents and images, to facilitate intelligent search and analysis. The proposed MetaOn framework involves, ontology-based information extraction and dat...

The visual senses for humans have a unique status, offering a very broadband channel for information flow. Visual approaches to analysis and mining attempt to take advantage of our abilities to perceive pattern and structure in visual form and to make sense of, or interpret, what we see. Visual Data Mining techniques have proven to be of high value...

The visual senses for humans have a unique status, offering a very broadband channel for information flow. Visual approaches to analysis and mining attempt to take advantage of our abilities to perceive pattern and structure in visual form and to make sense of, or interpret, what we see. Visual Data Mining techniques have proven to be of high value...

Recent efforts in spatial and temporal data models and database systems attempt to achieve an appropriate kind of interaction between the two areas. This paper reviews the different types of spatio-temporal data models that have been proposed in the literature as well as new theories and concepts that have emerged. It provides an overview of previo...

We study the problem of classification as this is presented in the context of data mining. Among the various approaches that are investigated, we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical...

We study the problem of classification as this is presented in the context of data mining. Among the various approaches that are investigated, we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical...

The purpose of this paper is to study the problem of pattern classification as this is presented in the context of data mining. Among the various approaches we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classificatio...

The visual senses for humans have a unique status, offering a very broadband channel for information flow. Visual approaches to analysis and mining attempt to take advantage of our abilities to perceive pattern and structure in visual form and to make sense of, or interpret, what we see. Visual Data Mining techniqueshave proven to be of high value...