We present PicTouRe – a picture-based tourism recommender. PicTouRe aims to mitigate people’s difficulties in explicitly expressing their touristic preferences, which is even more challenging in the initial phase of travel decision making. Addressing this issue, with PicTouRe we follow the idiom “a picture is worth a thousand words” and use pictures as a tool to implicitly elicit peoples’ touristic preferences. We describe the core concept of PicTouRe - the Generic Profiler, which in essence determines an explainable vector representation, i.e., touristic profile, given any picture collection as input. We showcase a user’s journey through PicTouRe and describe the steps behind. Finally, we present results of a first user study supporting our approach. PicTouRe is available under https://pictoprof.ec.tuwien.ac.at and a demo video under https://youtu.be/xZnXLPcenEs.

Eliciting the preferences and needs of tourists is challenging, since people often have difficulties to explicitly express them -- especially in the initial phase of travel planning. Recommender systems employed at the early stage of planning can therefore be very beneficial to the general satisfaction of a user. Previous studies have explored pictures as a tool of communication and as a way to implicitly deduce a traveller's preferences and needs. In this paper, we conduct a user study to verify previous claims and conceptual work on the feasibility of modelling travel interests from a selection of a user's pictures. We utilize fine-tuned convolutional neural networks to compute a vector representation of a picture, where each dimension corresponds to a travel behavioural pattern from the traditional Seven-Factor model. In our study, we followed strict privacy principles and did not save uploaded pictures after computing their vector representation. We aggregate the representations of the pictures of a user into a single user representation, i.e., touristic profile, using different strategies. In our user study with 81 participants, we let users adjust the predicted touristic profile and confirm the usefulness of our approach. Our results show that given a collection of pictures the touristic profile of a user can be determined.

In this paper we present the results of a user study focusing on social relationships within small groups. The goal is to better understand how to incorporate the information about social relationships in group recommendation models. Our analysis, conducted on a data set of 150 participants in 41 groups deciding on a travel destination to visit together, brings out some intriguing outcomes. We demonstrate that social centrality is hardly an indicator of the social influence in the decision-making process of "equality matching" types of groups. However, socially central group members and socially close groups are significantly happier with group decisions than those who are loosely related. Moreover, in this paper we show that social relationships are indicators of other concepts relevant in group settings, therefore in group recommender systems as well.

Most research on group recommender systems relies on the assumption that individuals have conflicting preferences; in order to generate group recommendations the system should identify a fair way of aggregating these preferences. Both empirical studies and theoretical frameworks have tried to identify the most effective preference aggregation techniques without coming to definite conclusions. In this paper, we propose to approach group recommendation from the group dynamics perspective and analyze the group decision making process for a particular task (in the travel domain). We observe several individual and group properties and correlate them to choice satisfaction. Supported by these initial results we therefore advocate for the development of new group recommendation techniques that consider group dynamics and support the full group decision making process.

Personalized recommendation strongly relies on an accurate model to capture user preferences; eliciting this information is, in general, a hard problem. In the field of tourism this initial profiling becomes even more challenging. It has been shown that particularly in the beginning of the travel decision making process, users themselves are often not conscious of their needs and are not able to express them. In this paper, the basics of a picture-based approach are introduced that aims at revealing implicitly given user preferences. Based on a set of travel related pictures selected by a user, an individual travel profile is deduced. This is accomplished by mapping those pictures onto seven basic factors that reflect different travel behavioral aspects. Also tourism products can be represented by this seven factor model. Thus, this model constitutes the basis of our recommendation algorithm. First tests show that this non-verbal way of interaction is experienced as exiting and inspiring.

Service-oriented architectures (SOA) aim at the alignment of business and IT by having a clear business process-centric focus. In order to reach that goal, real-world business processes are captured by business process models. These models serve as the basis for the declarative configuration of a SOA using appropriate deployment artifacts - i.e., XML-based process languages. Consequently, requirements engineering for SOAs must focus on business processes and on their integration into systems using interoperable services, which is not the case for most conventional requirements engineering approaches. In this paper we present a requirements engineering approach specifically designed for the engineering of SOAs. Requirements are captured using a unified process, based on phases and iterations eventually leading to a formalized and unambiguous requirements specification. The final requirements specification can be used in succeeding development phases - i.e. for the model-driven generation of deployment artifacts for SOAs. The presented solution is called [vem: xi:] and is successfully used in the IT department of a Mobile Network Operator (MNO) in Austria. In the highly volatile world of mobile communication the presented approach enables faster application development and faster integration of solutions, thus leading to a competitive advantage over other market participants.

Different approaches and programs for qualitative simulation are briefly reviewed to illustrate the characteristic features of QUALSIM, an object-oriented package for supporting the identification of the structure of dynamic systems. The package is based on a qualitative interface and a stochastic calculus using variables' ranges defined in the real number space. The intuitive way of defining variables and connections and the possibility of avoiding the definitions of equations linking the variables make it possible to use the package for fast model prototyping and as an educational tool. The identification of a model of lake eutrophication is shown as an example.>

A prototype of an on-line inventory of computer programs for environmental studies available at the Laboratorio di Informatica Territoriale ed Ambientale (LITA), Politecnico di Milano, is presented. The main purpose of this software base is to overcome some of the difficulties encountered is disseminating to a relatively wide range of potential users all the informations concerning programs already available. Each program description is stored in a structured, but easy to read format in order to allow a fast screening. The prototype software base has been implemented on a personal computer, using a commercial relational DMBS. Furthermore, a user-friendly interface, which has some intelligent features, has been designed in order to ease the use of the system.