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Understanding the users' needs is important for designing an application that provides a good usage experience. One can use design thinking (DT) to help identify those needs. Persona is a technique used in DT to support the requirements elicitation by describing user profiles. Nevertheless, the persona descriptions created using a traditional template may include many details about the users that are not relevant to the application design. To overcome this limitation, the authors proposed the PATHY technique to guide software engineers in creating and describing more useful personas, i.e. personas with information that is more relevant to the application design. They conducted an experiment to compare PATHY to another persona‐based technique which uses a traditional template and also supports the representation of the application's requirements. In this study, they assessed which of the two techniques helps to generate descriptions of personas that are more focused on potential requirements to consider in the design of the application. In addition, they analysed the efficiency of the techniques and the participants' perception of use. The results showed that PATHY generated more relevant characteristics for the application design than the technique that follows the traditional description. The PATHY was also more efficient for creating personas. [ABSTRACT FROM AUTHOR]

With the rapid growth of cell phone networks during the last decades, call detail records (CDR) have been used as approximate indicators for large scale studies on human and urban mobility. Although coarse and limited, CDR are a real marker of human presence. In this paper, we use more than 800 million CDR to identify weekly patterns of human mobility through mobile phone data. Our methodology is based on the classification of individuals into six distinct presence profiles where we focus on the inherent temporal and geographical characteristics of each profile within a territory. Then, we use an event-based algorithm to cluster individuals and we identify 12 weekly patterns. We leverage these results to analyze population estimates adjustment processes and as a result, we propose new indicators to characterize the dynamics of a territory. Our model has been applied to real data coming from more than 1.6 million individuals and demonstrates its relevance. The product of our work can be used by local authorities for human mobility analysis and urban planning. [ABSTRACT FROM PUBLISHER]

Now days, web search engines provide good services in terms of retrieval and presentation of the information to the user. A foremost difficulty in the modern and ever growing web is the lack of user interest adaption in the process of web search. All users are presented with the same set of search engine result pages (SERPs) for a given input query string, since it follows the keyword based search. The limitation of keyword based search is (i) uncertain user needs and (ii) improper query selection. If the programmer is searching for a query 'switch', it refers to the switch statement of a programming language and for an electrical engineer, the context of search is the physical house hold switch component. In addition to that a user may fall short in choosing the proper query for search that best articulate their information need. Hence, it is evident that keyword searches have tough time to distinguish the user context over the query. A typical approach to focus on this challenge is a personalized web search strategy where the results are retrieved based on the user interest and preferences. The three different major search modules are: (i) building user profiles (ii) re-ranking the SERPs in personal mode and (iii) re-ranking the SERPs in group mode. The proposed work stands for contributing in the field of user profile construction and personalized page ranking. A new method of user model representation termed as Preference Network is constructed. The proposed system can work in both initialization and maintenance mode to build a new or update an existing model. Both the short term and long term interest are utilized to rank the SERPs. The user interest score and group interest score are computed dynamically. [ABSTRACT FROM AUTHOR]

The aim of the present study was to better understand how public transport users make their choice of route, in order to favor the use of public transport (henceforth PT) in large cities. Based on decision-making theories, a classical choice paradigm (Slovic, 1975), and recent findings in psychology (Chowdhury & Ceder, 2013; Grison et al., 2016) we developed a new method to investigate the effect of contextual and individual factors on PT route choices. We proposed to sixty PT users realistic forced choices between two PT routes that differed in affective (level of physical comfort) and instrumental (number of transport modes) attributes. We also varied the context of the decision (long or short route; route to go to work, to a leisure activity, etc.), and we recorded various individual characteristics (age, sex, attitude towards PT, habits, etc.). Our results highlight that: the comfort of the route is preferred to the number of transport modes, especially for long trips; the choice of the comfortable alternative or the one with only one transport mode depends on user characteristics; the length of the trip and habits are the most important variables in the decision, but attitudes also seem to play a major role. Our study furthers current knowledge about the psychological process of PT route choice in light with multi-attribute choices theories, and provides new insights that can contribute to improving current large city route-planning aids. [ABSTRACT FROM AUTHOR]

In the context of e-government and more specifically that of parliament, this paper tackles the problem of finding Members of Parliament (MPs) according to their profiles which have been built from their speeches in plenary or committee sessions. The paper presents a common solution for two problems: firstly, a member of the public who is concerned about a certain issue might want to know who the best MP is for dealing with their problem (recommending task); and secondly, each new piece of textual information that reaches the house must be correctly allocated to the appropriate MP according to its content (filtering task). This paper explores both these ways of searching for relevant people conceptually by encapsulating them into a single problem: that of searching for the relevant MP’s profile given an information need. Our research work proposes various profile construction methods (by selecting and weighting appropriate terms) and compares these using different retrieval models to evaluate their quality and suitability for different types of information needs in order to simulate real and common situations. [ABSTRACT FROM AUTHOR]

Current debates on students' use of information and communication technology (ICT) have brought to attention profiles and purposes of ICT use in either school-related or recreational contexts. Examining these two contexts at the same time, the present study seeks to identify student profiles of ICT use on the basis of the Norwegian International Computer and Information Literacy Study (ICILS) 2013 data ( N = 2426). In order to explore profiles of ICT use in schools and at home for different purposes such as recreation, study purposes, exchanging information, and social communication, we take a person-centered approach and apply latent profile analysis. These analyses revealed two independent user profiles and showed that background characteristics (i.e., gender, immigration status) and motivational constructs (i.e., self-efficacy, interest, and enjoyment in ICT) play a significant role in determining profile membership. Significant differences between the user profiles in students' computer and information literacy test performance did not exist. Given that the coverage of ICT at home and in schools has increased substantially over the last decades, the identification of user profiles informs teachers and parents about whether or not students exploit these opportunities to the same extent. Implications for future research and practice are discussed. [ABSTRACT FROM AUTHOR]

Offices are transforming into multi-user, open space environments to stimulate interaction between people and optimize the usage of space. Due to design practices, lighting systems in these multi-user environments are implemented as a regular grid of luminaires that often does not match the furniture layout. Consequently, purely personal control over general lighting is not achievable in most cases. As a result, a single luminaire affects several neighbouring desks, creating shared lighting controls and conditions. Therefore, providing satisfying lighting conditions to everyone becomes a challenge. This paper proposes a first method for modelling lighting preference profiles of users based on their control behaviour and preference information. Based on objective measurements and subjective data obtained in two field studies, users can be profiled based on their control behaviour, regarding characteristics as activeness, dominance, lighting tolerance, and dimming level preference. The results show significant differences between lighting preference profiles of users. This paper also proposes a first method for discovering and triggering submissive users to express their preferences in order to derive their profiles as accurate as possible. This will help to secure users' comfort by offering satisfying lighting conditions to their preference. By knowing the lighting preference profiles of users, the probability of conflict between users can be predicted and minimized. [ABSTRACT FROM AUTHOR]

Nutiseadmeid kasutatakse sageli igapäevaelus, kuid ei ole teada, mil viisil ja kui laialdaselt rakendatakse neid õppimise eesmärgil. Selle väljaselgitamiseks korraldati ülevaateuuring, milles osales 3521 õpilast 6. ja 9. klassist. DIGCOMPi raamistikust lähtudes hindasid õpilased, kui sageli nad kasutavad nutiseadmeid õppimiseks loodusainetes ja matemaatikas. Õpilased jagati hierarhilise klasteranalüüsi abil viide rühma: sünnipärased digikodanikud, infoinimesed, suhtlevad infoinimesed, loomeinimesed ja nutiseadmete mittekasutajad. Neist nelja esimese profiilid iseloomustavad eri viisil nutiseadmete kasutajaid, keda on kokku ligikaudu pool valimisse kuulunud õpilastest. Teise poole moodustavad nutiseadmete mittekasutajad, kelle seas saab eristada täpsemaid alarühmi (kokku 11). Alarühmade võrdlemine võimaldab kavandada viise, kuidas kujundada nutiseadmete kasutamise harjumust. Samuti ilmneb uurimistulemustest, et 6. ja 9. klassi õpilased ning poisid ja tüdrukud kuuluvad eri rühmadesse erineva tõenäosusega. [ABSTRACT FROM AUTHOR]

Increasing public transport ridership while providing a service that better caters to individual travelers poses an important goal and challenge for society, particularly public transport authorities and operators. This study identifies and characterizes current and potential users of public transport in Sweden and identifies the most important determinants of travel satisfaction with Public Transport services for each segment of travelers. In addition, it investigates the changes over time of attribute importance among the different segments and the inter-segment geographical variation of overall satisfaction. The analysis is based on a dataset of almost half a million records. Travelers were clustered based on their socio-demographics, travel patterns and accessibility measures to enable the analysis of determinants of satisfaction for different market segments. The cluster analysis results with five segments of Swedish travelers include: (i) inactive travelers; (ii) long distance commuters; (iii) urban motorist commuters; (iv) rural motorist commuters and; (v) students. By contrasting satisfaction with the importance of each quality of service attribute, three key attributes that should be prioritized by stakeholders are identified: customer interface, operation, network and length of trip time . Interestingly, the results suggest an overall similarity in the importance of service attributes among traveler segments. Nevertheless, some noticeable differences could be observed. The quality of service attributes’ importance levels reveal overall changes in appreciations and consumption goals over time. The more frequent public transport user segments are more satisfied across the board and are characterized by a more balanced distribution of attribute importance while rural motorist commuters are markedly dissatisfied with service operation attributes. This work can help authorities to tailor their policies to specific traveler groups. [ABSTRACT FROM AUTHOR]

This work was a part of a broader empirical study of Internet users with excessive and dysfunctional Internet use symptoms. The aim of this particular article was to describe user profiles of Internet addicts in Serbia. The study recruited 100 subjects in total, 50 in both the clinical and control group. The clinical group included the Internet users who asked for professional help due to the symptoms of the excessive Internet use and fulfilled the diagnostic criteria for Internet behavior disorder proposed by the American Psychology Association. The results have shown that population with Internet addiction symptoms equally included both males and females, mostly adolescent and younger population, teenagers and university students, persons with higher income and users from economically more developed areas of Serbia. The user profile of this group is characterized by frequent logging on with intervals of several hours online at one time, mainly in the evening or at night, and also intensive negative reactions to any form of Internet access deprivation. By means of factor analysis, three dimensions of pathological use have been established: mixed type with particular need for up-to-date information, social interaction addiction and need for fun-seeking, namely pursuing hobbies online (cyberpornography, online games, music, art and so on).

The building's energy demand for heating significantly depends on many parameters of the building, also on the climate zone. To determine this demand, the technical parameters of the building as well as functional parameters and the associated temperatures to be maintained inside the building are usually adopted. The article proposes a methodology for assessing both economic and ecological benefits resulting from changing the user profile and thermal insulation performance. The balances of ecological benefits were analysed in accordance with the idea of sustainable development by adopting model residential buildings, taking into account the year of construction of the building, the type of heat source and thermal insulation, and five types of room user profiles, considering technical and social requirements. The research on the impact of changing the user profile shows that lowering thermal comfort always brings economic and ecological benefits. In the case of thermal insulation, despite the reduction of the building's heat demand, the balance of benefits and costs is always positive only in the ecological aspect. For economic reasons, the balance does not have to be positive (in Polish conditions), due to the high economic costs of thermal insulation. Assuming that users are willing to accept lower thermal comfort, a user profile with a lower temperature can be recommended for economic and ecological benefits, or a profile reduction including the performance of thermal insulation. The above approach has a significant social dimension when rationalizing expenditure on thermal modernization of buildings, especially in energy and economic poverty areas. The suggestion, resulting from the study, of changing our habits to high temperatures in living quarters, can largely contribute to the improvement of the state of the environment, but also have a significant impact on the savings of energy resources. Lowering the temperature in the rooms from 23 °C to 17 °C reduces the energy demand for heating by up to about 40%. • Methodology for assessing benefits resulting from changing the user profile. • Economic and ecological benefits of thermal insulation and changing the user profile. • The year of construction of the building and the type of heat source were considered. • Five types of room user profiles are included. • The balance of benefits and costs is always positive only in the ecological aspect. [ABSTRACT FROM AUTHOR]

The growing use of Social Networking Sites (SNS) around the world has made it necessary to understand individuals’ behaviours within these sites according to different cultures. Based on a comparative study between two different European countries (The Netherlands versus Spain), a comparison of typologies of networked Internet users has been obtained through a latent segmentation approach. These typologies are based on the frequency with which users perform different activities, their socio-demographic variables, and experience in social networking and interaction patterns. The findings show new insights regarding international segmentation in order to analyse SNS user behaviours in both countries. These results are relevant for marketing strategists eager to use the communication potential of networked individuals and for marketers willing to explore the potential of online networking as a low cost and a highly efficient alternative to traditional networking approaches. For most businesses, expert users could be valuable opinion leaders and potential brand influencers.

In this work we present our progress in the field of Intelligent User Profiling. Our objective is to build a user profile that captures users' skills rather than classical users' interests. Thus, we propose a novel approach to learn users' skills by observing their behavior during a very common activity: playing games. Specifically, we automatically identify users' skills to manage abstractions by using digital games. Abstraction skills identification is important because it is related to several behavioral tendencies such as career preferences, aptitudes, and learning styles. Traditional skills identification is based on questionnaires whose application implies many complications, including non-intentional influences in the way questions are formulated, difficulty to motivate people to fill them out, and lack of awareness of the consequences or future uses of questionnaires. To address these limitations, we built a user profile that collects users' actions when playing digital games. Then, we built and trained a Hierarchical Naive Bayes network to infer users' skills to manage abstractions. The experiments carried out show that digital games can help us to identify abstraction skills with a promising accuracy. [ABSTRACT FROM AUTHOR]

This article proposes Hefestos, an intelligent system applied to ubiquitous accessibility. This model uses ubiquitous computing concepts to manage accessibility resources for people with disabilities. Among the concepts employed, context awareness, user profiles and trails management can be highlighted. The paper proposes an ontology for accessibility and delineates scenarios of its application in everyday life of people with disabilities. Moreover, the implementation of a smart wheelchair prototype and its application in a practical experiment is described. Ten users with a range of disability degrees tried the system and filled out a survey based on the technology acceptance model. This experiment demonstrated the main functionalities and the acceptance of the system. The results showed 96 % of acceptance regarding perceived easy of use and 98 % in perceived usefulness. These results were encouraging and show the potential for implementing Hefestos in real life situations. [ABSTRACT FROM AUTHOR]

User profile inference on online social networks is a key task for targeted advertising and building recommender systems that rely on social network data. However, current algorithms for user profiling suffer from one or more of the following limitations: (1) assuming that the full social graph or a large training set of crawled data is available for training, (2) not exploiting the rich information that is available in social networks such as group memberships and likes, (3) treating numeric attributes as nominal attributes, and (4) not assessing the certainty of their predictions. In this paper, to address these limitations, we propose an algorithm named Partial Graph Profile Inference+ (PGPI+). The PGPI+ algorithm can accurately infer user profiles under the constraint of a partial social graph. PGPI+ does not require training, and it lets the user select the trade-off between the amount of information to be crawled for inferring a user profile and the accuracy the inference. Besides, PGPI+ is designed to use rich information about users when available: user profiles, friendship links, group memberships, and the 'views' and 'likes' from social networks such as Facebook. Moreover, to also address limitations 3 and 4, PGPI+ considers numeric attributes in addition to nominal attributes, and can evaluate the certainty of its predictions. An experimental evaluation with 31,247 user profiles from the Facebook and Pokec social networks shows that PGPI+ predicts user profiles with a higher accuracy than several start-of-the-art algorithms, and by accessing (crawling) less information from the social graph. Furthermore, an interesting result is that some profile attributes such as the status (student/professor) and genre can be predicted with more than 95 % accuracy using PGPI+. [ABSTRACT FROM AUTHOR]

The dramatic increase in the amount of information stored on the web makes it more important to familiarize people with disabilities and elderly people with digital devices and applications and to adapt websites to enable their use by these users. D iscapnet is a website mainly aimed at visually disabled people, and navigation is a challenging task for its users. In this context, system evaluation and problem detection become crucial aspects for enhancing user experience and may contribute greatly to diminishing the existing technological gap. This study proposes a system based on web-mining techniques that collects in-use information while the user is accessing the web (thus, being a noninvasive system). The proposed system models users in the wild and discovers navigation problems appearing in Discapnet and can also be used for problem detection when new users are navigating the site. The system was tested and its efficiency demonstrated in an experiment involving navigation under supervision, in which 82.6% of a set of disabled people were automatically labeled as having problems with the website. [ABSTRACT FROM AUTHOR]

Online health communities provide a rich source of expertise from experienced patients, but uncovering "peer mentors" with shared circumstances is like finding a needle in a haystack-a problem that will escalate as these communities grow and diversify.We investigated interactive health interest profiles (HIPs) that summarize health-related terms extracted from users' community posts. Through iterative design, we explored practical designs that accommodate differences in users' community participation in three HIP prototypes: Text, Word Cloud, and Timeline. By comparing prototype usability with patients and design experts, we found that patients accurately used each prototype but completed some tasks faster with the Timeline HIP. Despite this advantage, patients preferred the Text HIP. Design experts and patients agreed that simple data overviews and granular details with salient cues that invite interactivity are key design considerations for HIPs. Findings offer key design considerations for HIPs that patients find most useful when forging critical connections. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a system for automated learning directed towards discovering and enhancement of the set of recurrent behaviours that can be found within a learning knowledge base and how they can be modelled to enable a more effective reasoning and tactical strategies for personalized adaptation and decision making. Design/Methodology/Approach: The paper introduces a methodology that makes use of information readily available within a learning process to explore and analyse the data to obtain inference knowledge capable of enhancing individual learning performance. The author valuated this approach through a user-centric design prototype and a model developed using Business Process Model Notations to corroborate the focus on improving performance of e-learning systems. Findings: The technological response to satisfying the increasing demand for richer and more precise depiction of e-learning applications capable of providing platforms for pattern exploration where users can browse for knowledge they might consider as interesting is by providing a personalized adaptive learning system for the users. Adoption of such technological developments will spark a great success for many learners and needed to provide continuous intelligent recommendation, guidance and feedbacks on learner's performance especially in achieving the overall learning objective. Research limitations/implications: To meet the overall needs of intended users, there is requirement for e-learning systems to embody technologies that support learners in achieving their learning goals and this process do not happen automatically. Such process should take into account the fact that there is an additional task of matching these persons (user profiling) with solutions that best fits their particular learning needs (personalization). Practical implications: The work in this paper considers the implication of the user centered design approach, and to this end, identify some of the common design problems with e-learning systems as means to revealing the implications for designers to stick to user-centric standards when developing automated learning systems in order to ensure learners satisfaction and reliability. Originality/value: The approach and prototype described in this paper provides an enhanced model for learning which is useful towards the development of e-learning systems that are more intelligent, predictive and robotically adaptive, which also aid in discovery of new learning patterns and enhancement of existing learning processes. [ABSTRACT FROM AUTHOR]

This paper evaluates the quality of service of the metropolitan Metro of Seville (Spain) across different user profiles, as determined through cluster analysis. Service quality evaluation is performed using a composite index that combines the user point of view with the service operator point of view. The combination of these two types of service quality measurement fulfils the need to provide a reliable measurement tool for transit performance. Six user profiles were identified, and it was ascertained that they have different opinions about the service, with heterogeneous gaps between the points of view among the six user profiles. [ABSTRACT FROM AUTHOR]

The increasing of products, information and services based on users׳ profiles has made recommender systems to be increasingly present, easing the selection and retention of users in services on the Web. However, optimizations must be performed in such systems mainly regarding the modeling of users׳ profiles. Preferences are generally modeled superficially, due to the scarcity of data collected, as notes or comments, or the inductive information susceptible to errors. This manuscript proposes a recommender tool with three ensemble approaches based on multimodal interactions that combines different types of users׳ feedback processed individually by traditional recommendation algorithms. The approaches have been developed to improve the quality of predictions in recommender systems, considering a large number of user information. [ABSTRACT FROM AUTHOR]

Online communities are becoming an important tool in the communication and participation processes in our society. However, the most widespread applications are difficult to use for people with disabilities, or may involve some risks if no previous training has been undertaken. This work describes a novel social network for cognitively disabled people along with a clustering-based method for modeling activity and socialization processes of its users in a noninvasive way. This closed social network is specifically designed for people with cognitive disabilities, called Guremintza, that provides the network administrators (e.g., social workers) with two types of reports: summary statistics of the network usage and behavior patterns discovered by a data mining process. Experiments made in an initial stage of the network show that the discovered patterns are meaningful to the social workers and they find them useful in monitoring the progress of the users. [ABSTRACT FROM AUTHOR]

The features of popular social networking sites (SNSs) have been evolving rapidly. In this regard, there arise interesting questions that warrant investigations like, does user perception of SNSs get affected due to feature evolution of the SNSs? What features of the SNSs really matter to the users? Are features of SNSs important reasons for usage of these sites? In order to investigate these questions, the authors conducted an analytical study of SNSs usage in India. The study was undertaken with three stage qualitative process of detailed literature review, expert opinion elicitation followed by in-depth focus group discussions with 12 select panel of SNSs users. The study corroborates existing literature on SNS usage context in terms of usage purpose, usage impact due to user profile and age-group, user presence on different SNS platforms, and also shows some new findings on user perceptions on feature evolutions. [ABSTRACT FROM AUTHOR]