Personalized location prediction for group travellers from spatial-temporal trajectories

In recent years, research on location predictions by mining trajectories of users has attracted a lot of attentions. Existing studies on this topic mostly focus on individual movements, considering the trajectories as solo movements. However, a user usually does not visit locations just for the personal interest. The preference of a travel group has significant impacts on the places they have visited. In this paper, we propose a novel personalized location prediction approach which further takes into account users’ travel group type. To achieve this goal, we propose a new group pattern discovery approach to extract the travel groups from spatial-temporal trajectories of users. Type of the discovered groups, then, are identified through utilizing the profile information of the group members. The core idea underlying our proposal is the discovery of significant movement patterns of users to capture frequent movements by considering the group types. Finally, the problem of location prediction is formulated as an estimation of the probability of a given user visiting a given location based on his/her current movement and his/her group type. To the best of our knowledge, this is the first work on location prediction based on trajectory pattern mining that investigates the influence of travel group type. By means of a comprehensive evaluation using various datasets, we show that our proposed location prediction framework achieves significantly higher performance than previous location prediction methods

Constructing Identity and Heritage at the Crossroads: Albanian Families’ Cross-Border Connections and Homemaking Projects in Athens

Drawing from the author’s ethnographic/participatory work with Albanian families in Athens, this paper tells the story of two families constructing identity and heritage in Greece and Albania. The processes involved in the families’ literal and metaphorical connections with the ‘old country’, manifested in cross-border links, everyday routines and material cultures, are integral to their homebuilding projects in their new locale. Given families’ multiple-place-allegiance and disenfranchised status in a Greek context, theories on transnationalism and history and heritage from below are utilised in order to consider identity and heritage formation in the course of everyday routines. It is argued that the experience of building lives in more than two worlds results in the emergence of plurilocal identities, challenging spatially bounded notions of heritage

Behind the Circulations of Images

The history of images is nothing but a history of their mediums and a history of physical bodies. And hence, it is a history of circulation. As an introduction of this volume, this paper seeks to go behind the circulations of images by combining the fields of cultural, political and geopolitical studies, and by bringing together different methodologies from monographic and formal analysis to digital approaches (quantitative, cartographic, visual). These diversified case studies make it possible to answer three major questions: 1) How do images circulate? 2) Why do images circulate? 3) What does circulation do to an image and, more generally, to people

Geographic knowledge discovery from sparse GPS-data : Revealing spatio-temporal patterns of Amazonian river transports

A vast amount of spatio-temporal data has become available with the fast development of information technology and different monitoring systems over the last two decades. Position-aware devices are one of the most dominant sources for collecting movement data. Spatio-temporal information that is derived from the tracking devices enable to build movement patterns from the targets, and to calculate measurable motion parameters such as speed, change of speed or the direction of movement. This study utilized a specific pilot GPS-based monitoring system called Amazonian Riverboat Observation System (AROS) that was built to collect movement data of the local riverboats on the departments of Loreto and Ucayali in Peruvian Amazonia. AROS provides real-time GPS-data with coordinates and timestamp that indicate where and when the collaborating vessels are navigating. As an outcome of this thesis a specific analytical tool called Trajectory Reconstruction and Analysis Tool (TRAT) was developed. TRAT utilizes variety of geographic knowledge discovery methods to extract knowledge from movement data provided by AROS. Also spatio-temporal transportation characteristics in the study area were analyzed based on AROS data from the year 2012 and utilizing TRAT. This thesis focused on studying if there is seasonal and directional variation in transportation characteristics along the Amazonian rivers, and if river morphology affects the navigation. Also connection between water height of the rivers and travel speed of individual journeys was studied. Results of the thesis suggest that navigation along the rivers has seasonal and directional variation, and also the river morphology seems to affect the movement patterns of the vessels. On navigation route that was mostly meandering by river morphology, the downstream navigation was over 40% faster than upstream navigation during high water and intermediate, but during low water there was no difference between navigation directions. Seasonal variation was over 30% faster during high water compared to low water (on downstream direction). On upstream direction the navigation was fastest during low water but seasonal differences were considerably lower compared to downstream navigation. On navigation route that was mostly anastomosing by river morphology, the downstream navigation was approximately 20 % faster during the entire year. Results suggest that there is no seasonal difference in navigation characteristics along the larger and wider rivers, since the travel speeds were quite similar throughout the year. Fitting simple regression model between average travel speed of the journeys and water levels of the river revealed that there seems to be strong connection between travel speed and river height on the route along Ucayali river when travelled downstream (R2=0.73). On other cases that were studied, the results suggest that there is not connection between travel speed characteristics and river height. Comparing the results with earlier studies implied that the results of this thesis seemed to be fairly accurate. However, it is necessary to validate the results by doing cross-validations between data from different years observed with AROS. Transportation is in a key role when trying to find the factors affecting on development of a certain location. Thus transportation as means of accessibility has significant role in variety of contexts such as conversation, land use changes and deforestation. Results of this study could provide more accurate data for studies focusing on previously mentioned topics in the study area. Also utilization of TRAT in other contexts, such as studying global transportation patterns of professional vessels, could be possible by making few modifications to the tool.Informaatioteknologian ja erilaisten seurantajärjestelmien nopea kehitys viimeisten kahden vuosikymmenen aikana on mahdollistanut massiivisten spatio-temporaalisten tietovarantojen keräämisen. Paikannusteknologioilla varustetut laitteet ovat keskeisimpiä datalähteitä spatio-temporaalisen liikkumistiedon keräämiseen, ja tällainen data mahdollistaa erilaisten kohteiden (liikennevälineet, ihmiset jne.) liikkumisrakenteiden tutkimisen sekä erilaisten liikkumisparametrien kuten nopeuden, ja nopeuden sekä kulkusuunnan muutoksen laskemisen. Tässä tutkimuksessa hyödynnetään eristyistä pilotti-seurantajärjestelmää (AROS), joka on kehitetty keräämään jokilaivojen liikkumisdataa Loreton ja Ucayalin seuduilla Perun Amazoniassa. AROS mahdollistaa reaaliaikaisten laivojen sijantitietojen (koordinaatit) sekä aikatiedon (aikaleima) keräämisen. Tässä tutkimuksessa kehitettiin erityinen liikkumistiedonlouhintaan tarkoitettu analyysityökalu (TRAT), joka hyödyntää useita spatiaalisen tiedonlouhinnan menetelmiä informaation louhimiseksi AROS datasta. Tutkimuksessa tutkittiin, onko AROS datan perusteella jokinavigoinnissa nähtävissä vuodenaikaista vaihtelua vuoden 2012 aikana, ja vaikuttaako kulkusuunta sekä jokimorfologia navigointinopeuksiin. Tutkimuksessa tutkittiin myös, onko jokien vedenkorkeuksilla yhteyttä navigointinopeuksiin. Tutkimuksen tulokset osoittivat, että navigointi vaihtelee riippuen vuodenajasta sekä kulkusuunnasta, ja myös viitteitä jokimorfologian vaikutuksesta navigointiin oli paikoittain nähtävissä. Meanderoivilla jokiosuuksilla navigoiminen alavirtaan oli n. 40 % nopeampaa korkeanveden aikaan, mutta matalanveden aikaan eroa nopeuksissa ei ollut juuri nähtävissä. Vuodenaikaisvaihtelu oli selkeintä alavirtaan kuljettaessa, jolloin navigointi korkeanveden aikaan oli n. 30 % nopeampaa verrattuna matalanveden aikaan. Anastomoivilla jokiosuuksilla erot nopeuksissa eri kulkusuuntiin olivat vähäisemmät, ja navigointi oli keskimäärin 20 % nopeampaa alavirtaan (verrattuna ylävirtaan). Vuodenaikaisvaihtelua ei ollut juurikaan nähtävissä. Lineaarien regressiomalli jokikorkeuksien ja yksittäisten osareittien navigointinopeuksien välille osoitti, että yhteys oli selkeä (R2=0.73) osareiteillä, jotka kulkivat Ucayali-jokea alavirtaan. Muissa tutkituissa tapauksissa selkää yhteyttä ei löytynyt. Vertailemalla työn tuloksia aiempiin tutkimuksiin osoitti, että tulokset vaikuttavat olevan linjassa muiden tutkimusten tulosten kanssa. Työn tuloksia tulee jatkossa tosin vielä validoida vertailemalla vuoden 2012 tuloksia muiden vuosien tuloksiin AROS datan perusteella. Liikennejärjestelmät ovat keskeisiä tekijöitä, jotka vaikuttavat alueiden yleiseen kehitykseen. Yksi tapa kuvata liikennerakenteita on tarkastella paikkojen välistä saavutettavuutta, jolla on todettu olevan merkitystä lukuisiin eri yhteyksissä kuten maankäytön muutoksessa, deforestaatiossa sekä luonnonsuojelussa. Tämän tutkimuksen tulokset voivat tarjota tarkempaa dataa ja informaatiota liittyen edellämainittujen aiheiden tutkimiseen Perun Amazoniassa ja mahdolllisesti muillakin Amazonin alueilla. Kehitettyä analyysityökalua (TRAT) on myös mahdollista hyödyntää laajemmissa yhteyksissä, kuten globaalin laivaliikenteen tutkimuksessa, tekemällä pieniä muutoksia työkalun algoritmeihin

Harnessing the Power of the Arctic: Connecting tourists to nature through dog sledging activities.

This qualitative study explores the complex pockets of co-created interaction and throwntogetherness that produce meanings and value through an ethnographic sensory investigation of dog sledging tourism in Finnmark. I draw on a multirelational and multisensorial perspective on dog sledging, which means a holistic and socially constructed way of understanding Human-Animal Bonding (HAB) (DeMello, 2012). HAB enabled me to move beyond ethology when studying how culture, learning, emotions, communication, and cognition shaped interactions between tourist-mushers and dogs in arctic landscapes. The analysis unpacks the richness of the tourist-mushers interactions with sledge dogs by showing how physical senses and the arctic landscape bring about emotions and behavioural changes. The three main themes revolved around how the tourist-musher, through dog sledging, disconnected from everyday life and were reconnected with arctic landscapes. Theme one bonding, co-creation and interaction, consisting of the sub-themes bonding, co-creation and interactions, revealed pockets of meaning and value. Theme two, rhythm, through the sub- themes of time and flow, exposed the interconnectedness of reflection. Theme three, discovery mechanisms, with the sub-themes of physical senses, emotion, and learning, identified emotions of trust and empathy as learning tools that led to memory-making and mindfulness. I conclude that dog sledging tourism is a unique symbolic practice where nothing comes closer to experiencing nature's power. My study's symmetrical agency of humans and non-humans revealed new embodied ways of knowing. This knowledge strengthened and supported an embodied tourist experience approach (Everingham et al., 2021). Through my sensory ethnography of human and non-human encounters travelling together in nature, I address a research gap going beyond the advancement of Finnmarks’ regional tourism in Norway to a global understanding of what Arctic is. Keywords Dog sledging, Embodiment, Ethnography, Arctic landscape, Human-animal bonding, Relational materialis

Multiple-Aspect Analysis of Semantic Trajectories

This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full papers presented were carefully reviewed and selected from 12 submissions. They represent an interesting mix of techniques to solve recurrent as well as new problems in the semantic trajectory domain, such as data representation models, data management systems, machine learning approaches for anomaly detection, and common pathways identification

Distributed mining of convoys in large scale datasets

Tremendous increase in the use of the mobile devices equipped with the GPS and other location sensors has resulted in the generation of a huge amount of movement data. In recent years, mining this data to understand the collective mobility behavior of humans, animals and other objects has become popular. Numerous mobility patterns, or their mining algorithms have been proposed, each representing a specific movement behavior. Convoy pattern is one such pattern which can be used to find groups of people moving together in public transport or to prevent traffic jams. A convoy is a set of at least m objects moving together for at least k consecutive time stamps where m and k are user-defined parameters. Existing algorithms for detecting convoy patterns do not scale to real-life dataset sizes. Therefore in this paper, we propose a generic distributed convoy pattern mining algorithm called DCM and show how such an algorithm can be implemented using the MapReduce framework. We present a cost model for DCM and a detailed theoretical analysis backed by experimental results. We show the effect of partition size on the performance of DCM. The results from our experiments on different data-sets and hardware setups, show that our distributed algorithm is scalable in terms of data size and number of nodes, and more efficient than any existing sequential as well as distributed convoy pattern mining algorithm, showing speed-ups of up to 16 times over SPARE, the state of the art distributed co-movement pattern mining framework. DCM is thus able to process large datasets which SPARE is unable to.SCOPUS: ar.jDecretOANoAutActifinfo:eu-repo/semantics/publishe