Richard Schaller

RecSys for distributed events: investigating the influence of recommendations on visitor plans

Distributed events are collections of events taking place within a small area over the same time period and relating to a single topic. There are often a large number of events on offer and the times in which they can be visited are heavily constrained, therefore the task of choosing events to visit and in which order can be very difficult. In this work we investigate how visitors can be assisted by means of a recommender system via 2 large-scale naturalistic studies (n=860 and n=1047). We show that a recommender system can influence users to select events that result in tighter and more compact routes, thus allowing users to spend less time travelling and more time visiting events.

Detecting Event Visits in Urban Areas via Smartphone GPS Data

In geographic search tasks, where the location of the user is an important part of the task context, knowing whether or not a user has visited a location associated with a returned result could be a useful indicator of system performance. In this paper we derive and evaluate a model to estimate, based on user interaction logs, GPS information and event meta-data, the events that were visited by users of a mobile search system for an annual cultural evening where multiple events were organised across the city of Munich. Using a training / testing set derived from 111 users, our model is able to achieve high levels of accuracy, which will, in future work, allow us to explore how different ways of using the system lead to different outcomes for users.

Social event network analysis: structure, preferences, and reality

This paper focuses on the analysis of socio-spatial data, i. e., user-performance relations at a distributed event. We consider the data as a bimodal network (i. e., model it as a bipartite graph), and investigate its structural characteristics towards a social network. We focus on plans of the participants (expressed by preferences) and their fulfilment, and propose measures for matching preference and reality. We specifically analyse behavioural patterns w.r.t. distinct user and performance groups. We utilise real-world data collected at the Lange Nacht der Musik (Long Night of Music) 2013 in Munich.

Tell me your needs: assistance for public transport users

Providing navigation assistance to users is a complex task generally consisting of two phases: planning a tour (phase one) and supporting the user during the tour (phase two). In the first phase, users interface to databases via constrained or natural language interaction to acquire prior knowledge such as bus schedules etc. In the second phase, often unexpected external events, such as delays or accidents, happen, user preferences change, or new needs arise. This requires machine intelligence to support users in the navigation real-time task, update information and trip replanning. To provide assistance in phase two, a navigation system must monitor external events, detect anomalies of the current situation compared to the plan built in the first phase, and provide assistance when the plan has become unfeasible. In this paper we present a prototypical mobile speech-controlled navigation system that provides assistance in both phases. The system was designed based on implications from an analysis of real user assistance needs investigated in a diary study that underlines the vital importance of assistance in phase two.

Mobile tourist guides: bridging the gap between automation and users retaining control of their itineraries

We present a mobile tourist guide for planning and conducting sightseeing day trips. Users are provided different means to access and select the available sights, events and other points of interest (POIs): Via a hybrid recommender system, via browsing by sight category, via searching over descriptions of POIs or via browsing on a map. Based on users selection a route planner for time-constrained activities generates route suggestions taking additional constraints for public transport connections into account. A novelty of the implemented approach compared to existing solutions for tourists is that the user retains full control over the tour by diverse interaction possibilities: Before route generation different means for selecting POIs are provided, during route generation multiple route variants are suggested and after route generation users are able to directly edit any detail at any time, even if there are existing constraints that hinder the direct execution of an edit operation. Moreover, recommender, planner and editing are closely interconnected: Recommendations are used by the planner to fill-up unavoidable gaps. This may also be initiated manually during editing where also parts of the planner are involved to permit only those edits that keep the route feasible. The app is currently tailored to the city of Nuremberg but can be extended for other cities as well.

ROSE – Auf dem Weg zur mobilen Assistenz

ZusammenfassungROSE (Routing Service) ist ein vom BMWI im Rahmen des Förderprogramms INNONET gefördertes interdisziplinäres Forschungsprojekt mit dem Ziel, ein System zu entwickeln, das eine Empfehlungskomponente, eine Fußgänger-Navigationslösung und eine Anbindung an den öffentlichen Personennahverkehr (ÖPNV) kombiniert.

Mobile tourist guide: bridging the gap between recommending, planning and user-centered interaction

We present a mobile tourist guide for planning and conducting sightseeing day trips. The system combines a hybrid recommender system for sights, events and other points of interest with a tour planner for time-constrained activities taking additional constraints for public transport connections into account. A novelty of the implemented approach compared to existing solutions for tourists is that the user retains full control over the tour by being able to directly edit any detail at any time, even if there are existing constraints that hinder the direct execution of an edit operation. Moreover, recommender and planner are closely interconnected by regarding the reachability of recommended items with respect to the current selection as well as filling unavoidable gaps with fitting recommendations. The application is tailored to the city of Nuremberg, Germany, but can be extended by additional data for other destinations as well.