# Service-Aware Interactive Presentation of Items for Decision-Making
## 1 Introduction
On the other hand, it supports the development of agnostic presentation models that can be applied on top of different information filtering techniques in order to enrich them with an efficient presentation of their results. Both aspects contribute to improve information exploration support tools with a better presentation of results. The INTERactivE viSualizaTion (INTEREST) model, described in this paper, implements the previously discussed points. INTEREST provides a holistic, visual summary of consumer feedback based on interactive charts that support the analysis of reviews and their inspection at different temporal and content granularity levels to satisfy individual information needs. Building on the large availability of reviews in online catalogs of products and services (e.g., Amazon [21] and Yelp [22]), and on the existing literature on service design and evaluation, our model provides a synthesis of the satisfaction with items under multiple evaluation dimensions associated with consumer experience. Specifically, INTEREST is based on one of the most used conceptual models for the design and description of user experience, the \"Service Journey Maps\" [23; 24], which support the definition of high-level aspects of a service associated with different stages of fruition by users. In our model we define the evaluation dimensions as follows. * First, we model the user experience in stages, e.g., considering online product sales, the experience starts with searching for goods on the web site of the retailer and ends with after sales assistance. * Then, starting from the above stages, we identify a set of evaluation dimensions for item selection. * Finally, we extract the sentiment of online reviews with respect to the identified dimensions in order to automatically build a holistic synthesis of consumer feelings towards items. The interactive charts generated by INTEREST summarize previous consumers' opinions about the service evaluation dimensions. Moreover, they support a direct access to relevant reviews by highlighting the evaluated dimensions for easy identification. This enhances user awareness by supporting the formation of a personal opinion about items. In fact, the user can overview the search results focusing on the dimensions of interest, and (s)he can go in depth if (s)he is interested in specific data, being helped to identify the relevant text to be read. The definition of service evaluation dimensions for item presentation is a novel aspect of our approach: while some existing works provide diagrams to visually summarize low-level properties of items (see, e.g., in [25]), they cannot describe items in the holistic perspective given by service design. Notice also that, as INTEREST works on a set of items without making any assumptions about how they have been retrieved, it can be applied to explore the results of a recommendation algorithm, as well as of a faceted exploration system. This is a very important aspect because it makes it possible to exploit our model as a complement to any existing information filtering technology. INTEREST can be instantiated on different domains, after having analyzed the underlying services and evaluation dimensions. In our work we applied INTEREST to home booking and we tested it on a dataset of reviews gathered from Airbnb [26]. The resulting application, named Apartment Monitoring, enables the user to search for homes and to analyze reviews by focusing on different dimensions of the overall service experience, such as the appreciation of the host by her/his guests and the in-apartment experience. We designed a Service Journey Map describing the stages of a typical home renting experience from the viewpoint of the guest. Then, for each stage, we identified the evaluation criteria to be modeled in the application starting from those found in the literature about home and hotel booking [27; 28; 29]. Finally, we detected a set of relevant evaluation dimensions with respect to the service stages.