Personalized location-based brokering using an agent-based intermediary architecture

Tewari, Gaurav; Youll, Jim; Maes, Pattie

doi:10.1016/s0167-9236(02)00076-3

Cited by 68 publications

(30 citation statements)

References 3 publications

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“…The context means information which can be a feature of environment such as time and a location. For example, a context-aware restaurant recommendation system [4,5] can suggest appropriate restaurants to users based on their current location [6] and time [4].…”

Section: Related Workmentioning

confidence: 99%

Mobile game recommendation using touch gestures

Yang

Chen

Hong

et al. 2013

2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)

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Abstract-Today, any Internet user can find out and download more than one hundred thousands of games on mobile app marketplaces; nevertheless, how to pick the best games out of the large pool without spending much time on tryout is very challenging. The common rank list and social recommendation approaches for discovering new games do not work well when a player wants to search for games with a particular gameplay, or he may want to find out all the slow-paced games suitable for his grandparents. There is currently no feasible way to do that because these requirements cannot be formulated in a proper text search query.In this paper, we propose a scheme that can discover mobile games with similar gameplay based on players' touch gestures while playing a game. We select 22 mobile games from 5 genres and recorded 94 touch gesture traces from 5 subjects. The evaluation results show that 1) touch gestures can serve robust signatures of gameplay as the key traits of the touch gestures from different subjects remain consistent; 2) our scheme can give reasonably accurate recommendations of similar games simply based on touch gestures.

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Section: Related Workmentioning

confidence: 99%

Mobile game recommendation using touch gestures

Yang

Chen

Hong

et al. 2013

2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)

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“…The research on agents and MAS has been on the rise over the last two decades. The stream of research on IS and enterprise integration (Lei et al 2002;Kang and Han 2003;Tewari et al 2003) makes the MAS paradigm appropriate platform for integrative decision support within IS. Similarities between the agent in the MAS paradigm and the human actor in business organisations in terms of their characteristics and coordination lead us to a conceptualisation where agents in MAS are used to represent actors in human organizations.…”

Section: Some Background On Decision Support Multi-agent Systems Andmentioning

confidence: 99%

“…Similarities between the agent in the MAS paradigm and the human actor in business organisations in terms of their characteristics and coordination lead us to a conceptualisation where agents in MAS are used to represent actors in human organizations. Several approaches (Tewari et al 2003;Rivest et al 2005;Kishore et al 2006;Soo et al 2006) deal with agent support for integration and decision support. Research in (Kishore et al 2006) has shown that MAS paradigm provides an excellent approach for modelling and implementing integrated business IS.…”

Section: Some Background On Decision Support Multi-agent Systems Andmentioning

confidence: 99%

Ontology‐based Multi‐agent System to Support Business Users and Management / Daugiaagentine Sistema Grindžiama Ontologija Verslo Vartotojams Ir Vadybininkams Paremti

Lavbič

Vasilecas

Rupnik

2010

Technological and Economic Development of Economy

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Abstract. For some decision processes a significant added value is achieved when enterprises' internal Data Warehouse (DW) can be integrated and combined with external data gained from web sites of competitors and other relevant Web sources. In this paper we discuss the agent-based integration approach using ontologies (DSS-MAS). In this approach data from internal DW and external sources are scanned by coordinated group of agents, while semantically integrated and relevant data is reported to business users according to business rules. After data from internal DW, Web sources and business rules are acquired, agents using these data and rules can infer new knowledge and therefore facilitate decision making process. Knowledge represented in enterprises' ontologies is acquired from business users without extensive technical knowledge using user friendly user interface based on constraints and predefined templates. The approach presented in the paper was verified using the case study from the domain of mobile communications with the emphasis on supply and demand of mobile phones.

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“…The final hybrid recommendation result must be presented according to the characteristic of user's mobile device. Nowadays, we can find many mobile recommendation algorithms [1], [2] and hybrid recommender approaches [3], [4], [5] suitable for mobile environment Today the internet technologies continue to develop, popularity of mobile terminals to increase, and the quantity of information on the internet is immense and increasing each day. These qualities make mobile agents useful for the information-rich and communication-rich environment such as M-Commerce.…”

Section: Introductionmentioning

confidence: 99%