Hannes Werthner | Tu Wien (original) (raw)

Papers by Hannes Werthner

De Gruyter eBooks, Jul 24, 2023

CABI eBooks, 2006

Interface metaphors are credited with the capability of facilitating interface usability and lear... more Interface metaphors are credited with the capability of facilitating interface usability and learnability from the human-computer interaction (HCI) perspective. On travel-related websites, they can help travellers plan their trips and make the trip-planning process more entertaining and engaging. This chapter conceptualizes interface metaphors on travel-related websites by examining the functional roles they play. Implications for research on interface metaphors and travellers&amp;#39; trip-planning experience are also discussed.

This part describes the basic approaches used in qualitative reasoning as well as the underlying ... more This part describes the basic approaches used in qualitative reasoning as well as the underlying qualitative calculus and the different dimensions of mapping a quantitative model onto a qualitative one. Additionally, we provide a first classification of these methods. We separate the description of the modeling perspectives of the respective approaches in the next chapter from the detailed discussion of their specific reasoning techniques in chapter II.4 in order to underline the basic principles and their differences. However, also short descriptions of the reasoning mechanisms are provided in the first chapter. We use the following notation: if x denotes a variable or quantity in a numerical model, [x] or x denotes its qualitative equivalent. The same is true for operations: addition becomes ⨁, multiplication ⨂ and so on.6

International Conference on Electronic Commerce, Aug 19, 2008

Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising

Information and Communication Technologies in Tourism 2020, 2019

In this paper, we present the results of a user study focusing on the impact of group diversity o... more In this paper, we present the results of a user study focusing on the impact of group diversity on the group decision-making process, in the travel and tourism domain, when a group is faced with a task to select a destination that they would visit together. Firstly, motivated by previous research, we introduce several measures that capture diversity with respect to group members’ individual, explicit preferences. Next, we illustrate that group diversity in terms of preferences, in essence, has a negative effect on the group performance and the individual “well being”. The analysis was conducted upon two data sets, one containing information about 200 participants organized in 55 groups, and the second about 150 participants organized in 41 groups.

Information and Communication Technologies in Tourism 2018, 2017

The amount of people using online platforms to book a travel accommodation has grown tremendously... more The amount of people using online platforms to book a travel accommodation has grown tremendously. Hence, tour operators implement recommender systems to offer most suitable hotels to their customers. In this paper, a method of using hotel descriptions for recommendation is introduced. Different natural language processing methods were applied to pre-process a corpus of hotel descriptions. Further, three machine learning approaches for the allocation of hotel descriptions to travel behavioural patterns were implemented: clustering, classification and a dictionary-based approach. The main results show that clustering cannot be used in this context since the algorithm mostly relies on the operator-dependent structure of the descriptions. Supervised classification achieves the highest precision for six travel patterns, whereas the dictionary approach works best for one pattern. In general, the results for the different travel patterns vary due to the unequally distributed data sets as well as various characteristics of the patterns.

2019 IEEE 21st Conference on Business Informatics (CBI), 2019

The goal of recommender systems is, in essence, to help people to discover items they might like,... more The goal of recommender systems is, in essence, to help people to discover items they might like, i.e., items that fit their preferences, personality, and needs. Depending on the respective domain, those items can be books, movies, music, hotels, and much more. Typically, recommendations are based on past user interactions (e.g., movies a user saw, hotels a user booked, etc.). This work in progress paper focuses on news recommender systems. Because of the nature of news (e.g., constantly new items, short item lifetime, etc.), recommendations based on past interactions are especially hard to make. Hence, news recommender systems heavily rely on the actual content of news. While previous work mainly considers one aspect of the content of news articles, we jointly analyse and discuss in this work a given corpora of news articles on three different levels (i.e., document-level, topic-level, and author-level). The overall aim is to set to provide the basis for a comprehensive news recommender system, which reaches beyond accuracy and considers also diversity and serendipity. We demonstrate that relevant information can be extracted out of a given corpora, and differences in author, time, and topic can be shown. Furthermore, the author-level analysis shows that documents can be clustered based on the writing style of authors. Finally, our findings show that author-level analysis has the potential to recommend the most diverse items compared to the other approaches.

Tourism is an information intensive domain, where recommender systems have become an essential to... more Tourism is an information intensive domain, where recommender systems have become an essential tool to guide customers to the right products. However, they are facing major challenges, since tourism products are considered as complex and emotional. It has been shown that the seven-factor model is a legitimate way to counter some of these challenges. However, in order to recommend an item, it has also to be described in terms of this model. This work’s aim is to find a scalable way to map tourism destinations, defined by their attributes, to the seven-factor model. Through statistical analysis and learning methods it is shown that there is a significant relationship between particular destination features and the seven-factors and that destinations can be grouped in a meaningful way using their attributes.

2018 IEEE 20th Conference on Business Informatics (CBI), 2018

In this paper we analyze descriptions of group decision-making processes provided by 200 individu... more In this paper we analyze descriptions of group decision-making processes provided by 200 individuals organized in 55 groups. The goal of the paper is to show how such an analysis can be used when designing more efficient group recommender systems. To this end, we demonstrate that a) the provided group decision-making process descriptions can be systematically characterized by certain qualitatively identified aspects, b) the decision-making process that is adopted by a specific group is related to the characteristics of individuals in that group as well as to the characteristics of the group as a whole, and c) the decision reaching approach that a group naturally adopted can be determined, to a considerable extent, by certain characteristics of the group. Therefore, by examining real groups in a natural scenario, we can learn how a group recommender system should adapt when supporting group decision-making processes.

Information and Communication Technologies in Tourism 2017, 2017

The goal of the present study was to investigate how satisfied individuals are with the final out... more The goal of the present study was to investigate how satisfied individuals are with the final outcome of a group decision-making process on a joint travel destination. Using an experimental paradigm (N total = 200, N groups = 55) it was obvious to hypothesize that individuals would especially be satisfied with the final group decision when it matched their own initial travel preference and that they would be dissatisfied in case it mismatched their initial preference. However, in addition the influence of personality and group dynamics differences (Thomas-Kilmann Conflict Mode Instrument, Five Factor Model) as well as travel types of the individual decision maker on the satisfaction level with the group decision outcome as the dependent variable were further researched. The paper concludes with implications for e-tourism, especially with regards to the development of interactive tools for group travel.

Information and Communication Technologies in Tourism 2017, 2017

This paper addresses the challenges to support tourists in their decision-making during the pre-t... more This paper addresses the challenges to support tourists in their decision-making during the pre-trip phase and to facilitate the process of identifying those tourism objects that best fit the tourists’ preferences. The latter directly depends on the quality of the matchmaking process, i.e. finding those tourism objects that are most attractive to a particular tourist. To achieve this goal, an innovative approach is introduced that matches tourist profiles with the characteristics of tourism objects in order to obtain a ranked list of appropriate objects for a particular tourist. The matchmaking process leverages tourist factors as a shortcut to propose a first user profile and related to this, a first set of tourism objects. User feedback is then used to dynamically adapt the tourist profile and thus refine the set of recommended objects. Our approach is tested through a prototypical recommender system that suggests tourists in Vienna attractions that are tailored to their personal needs. Furthermore, a user study is conducted by asking people to interact with the system and fill in a questionnaire afterwards.

Information and Communication Technologies in Tourism 1999, 1999

Data Mining is a growing discipline in data analysis, linking data management with statistical me... more Data Mining is a growing discipline in data analysis, linking data management with statistical methods. Discovering new patterns or assuring behaviour that has been observed over the years is a central information for a company or an organisation. This is especially true for the field of tourism, where great volumes of data are collected, but not often analysed in depth. The paper presents an application of several techniques used in the field of Data Mining on the “Tux-database” of the tourism resort Tux in Tyrol, Austria. This database is based on the entities of the registration sheets in this tourism resort. Times series models of seasonal decomposition as well as simple descriptive procedures were used to detect primary pattern. In a second step explorative multivariate statistical techniques such as clustering, log-linear models and decision trees were applied to underline the primary results and to discover new ones.

Information Technology and Tourism — A Challenging Relationship, 1999