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68
Contextaware places of interest recommendations for mobile users
- in Proc. of DUXU’11, ser. LNCS
, 2011
"... Abstract. Contextual knowledge has been traditionally used in Recommender Systems (RSs) to improve the recommendation accuracy of the core recommendation algorithm. Beyond this advantage, in this paper we argue that there is an additional benefit of context management; making more convincing recomme ..."
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Cited by 18 (1 self)
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Abstract. Contextual knowledge has been traditionally used in Recommender Systems (RSs) to improve the recommendation accuracy of the core recommendation algorithm. Beyond this advantage, in this paper we argue that there is an additional benefit of context management; making more convincing recommendations because the system can use the contextual situation of the user to explain why an item has been recommended, i.e., the RS can pinpoint the relationships between the contextual situation and the recommended items to justify the suggestions. The results of a user study indicate that context management and this type of explanations increase the user satisfaction with the recommender system. 1
Supporting Travel Decision Making Through Personalized Recommendation
, 2004
"... We present an approach to the design of personalized recommender systems that integrates content-based methods, collaborative filtering techniques and case-based reasoning while adopting a user-centered perspective. These techniques are employed to support information search and choice processes. In ..."
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Cited by 16 (0 self)
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We present an approach to the design of personalized recommender systems that integrates content-based methods, collaborative filtering techniques and case-based reasoning while adopting a user-centered perspective. These techniques are employed to support information search and choice processes. In this framework, we developed and tested a system prototype (NutKing) that helps the user to construct a travel plan by recommending attractive travel products or by proposing complete itineraries. In the information search phase, the system aids the user in specifying a successful query that winnows out unwanted products in electronic catalogues and reduces the information overload. This is accomplished through two kinds of query rewriting operators (relaxation and tightening) in a mixed initiative approach. In the choice phase, the search results are sorted according to a case-base similarity metric, which takes into account the similarity between the users' travel preferences. The aim of this adaptive sorting is to highlight products that are potentially interesting, because they are similar to those selected by other users in an analogous context. The prototype has been empirically evaluated in a pilot study. The results of the pilot evaluation are discussed, with special reference to aspects concerning the usersystem interaction aspects.
A critical evaluation of location based services and their potential
- JOURNAL OF LOCATION BASED SERVICES EDITORIAL LEAD PAPER
"... This Editorial lead paper for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices ..."
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Cited by 16 (0 self)
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This Editorial lead paper for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices will emerge means that much research is needed to inform these developments. The paper reviews firstly: the science and technology of positioning, geographic information science, mobile cartography, spatial cognition and interfaces, information science, ubiquitous computing; and secondly the business, content and legal, social and ethics aspects, before synthesising the key issues for this new field.
Case-studies on exploiting explicit customer requirements in recommender systems
- USER MODELING AND USER-ADAPTED INTERACTION: THE JOURNAL OF PERSONALIZATION RESEARCH, A. TUZHILIN AND B. MOBASHER (EDS.): SPECIAL ISSUE ON DATA MINING FOR PERSONALIZATION
, 2009
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On-Tour Interactive Travel Recommendations
- In Information and Communication Technologies in Tourism 2004, Proceedings of the International Conference
, 2004
"... Travelers who access the Internet through currently available web information systems often experience difficulty in selecting interesting products. This is especially true for on-the-move travelers who browse information repositories using mobile devices with poor user interfaces. Travelers suffer ..."
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Cited by 11 (3 self)
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Travelers who access the Internet through currently available web information systems often experience difficulty in selecting interesting products. This is especially true for on-the-move travelers who browse information repositories using mobile devices with poor user interfaces. Travelers suffer from an overload of information and options to consider, and they lack system support in filtering information and comparing products. In this paper, we propose an innovative approach to the problem of mapping travelers ’ needs to a convenient set of travel products or services. In particular, we present an on-the-move restaurant recommender system (mITR) integrated with a pre-travel planning aid system (NutKing). In this approach, firstly, the knowledge contained in a repository of past user choices is exploited to initialize the recommendation process with a set of implicit preferences. Secondly, to minimize user efforts in building a precise search query, we do not require the user to formulate a query at the beginning of the interaction, rather we involve her in a dialogue where the traveler is encouraged to provide critiques and feedback to the system recommendations. These critiques are then incorporated by the system into a new query that tries to better model the user preferences. The approach has been validated empirically by a set of users.
Designing Recommender Systems for Tourism
"... In this paper, we argue that the process of developing travel recommender systems (TRS) can be simplified. By studying the application domain of tourism information systems, and examining the algorithms and architectures available for recommender systems today, we discuss the dependencies and presen ..."
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In this paper, we argue that the process of developing travel recommender systems (TRS) can be simplified. By studying the application domain of tourism information systems, and examining the algorithms and architectures available for recommender systems today, we discuss the dependencies and present a methodology for developing TRS, which can be applied at very early stages of TRS development. The methodology aims to be insightful without overburdening the project team with the mathematical basis and technical detail of the state of the art in recommender systems and give guidance on design choices to the project team.
Utilizing Facebook Single and Cross Domain Data for Recommendation Systems
"... The emergence of social networks and the vast amount of data that they contain about their users make them a valuable source for personal information about users for recommender systems. In this paper we investigate the feasibility and effectiveness of utilizing existing available data from social n ..."
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Cited by 7 (0 self)
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The emergence of social networks and the vast amount of data that they contain about their users make them a valuable source for personal information about users for recommender systems. In this paper we investigate the feasibility and effectiveness of utilizing existing available data from social networks for the recommendation process, specifically from Facebook. The data may replace or enrich explicit user ratings. We extract from Facebook content published by users on their personal pages about their favorite items and preferences in the domain of recommendation, and data about preferences related to other domains to allow cross- domain recommendation. We study several methods for integrating Facebook data with the recommendation process and compare the performance of these methods with that of traditional collaborative filtering that utilizes user ratings. In a field study that we conducted, recommendations obtained using Facebook data were tested and compared for 95 subjects and their crawled Facebook friends. Encouraging results show that when data is sparse or not available for a new user, recommendation results relying solely on Facebook data are at least equally as accurate as results obtained from user ratings. The experimental study also indicates that enriching sparse rating data by adding Facebook data can significantly improve results. Moreover, our findings highlight the benefits of utilizing cross domain Facebook data to achieve improvement in recommendation performance.
An automated itinerary planning system for holiday travel
- Information Technology and Tourism
, 2004
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Constraint-based recommendation in tourism: A multi-perspective case study
- INFORMATION TECHNOLOGY & TOURISM
, 2009
"... In many business-to-consumer (B2C) e-commerce scenarios, recommender systems (RS) have been shown to be valuable tools both for the online customer and the merchant. Such systems help customers find interesting items in large product assortments, increasing the chance of immediate online purchases a ..."
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Cited by 6 (2 self)
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In many business-to-consumer (B2C) e-commerce scenarios, recommender systems (RS) have been shown to be valuable tools both for the online customer and the merchant. Such systems help customers find interesting items in large product assortments, increasing the chance of immediate online purchases and fostering long-term customer loyalty. However, standard technologies from classical RS application domains such as books and movies cannot be directly adopted in the tourism domain. This article presents a case study of a constraint-based RS that was integrated into a travel advisory system for an Austrian spa resort. The study analyzes the system and its environment from three perspectives. First, technological aspects of system development and maintenance are discussed; second, corresponding to the supplier’s view, the end user’s perspective is analyzed based on the findings of a study of the system’s usability and the perceived customer utility. Finally, the effectiveness of the system’s ability to positively affect user behavior is evaluated and discussed. The findings show that constraint-based RS not only help positively influence tourist behavior, but such systems can be built cost-effectively when using appropriate knowledge acquisition and maintenance tools. Key words: Recommender systems; Constraint-based recommendation; Conversational recommender systems; Web personalization offer personalized information and its information filtering functionality. In addition to this core functionality that supports in particular customers making decisions in domains complicated by large product assortments, RS are also supposed to in-crease the quality of the perceived shopping experience. Depending on the technology used, RS can
