samap: An user-oriented adaptive system for planning tourist visits

Castillo, Luis; Armengol, Eva; Onaindía, Eva; Sebastiá, Laura; Boticario, Jesús G.; Rodríguez, Antonio Pérez; Fernández, Susana; Arias, Juan Diego Betancur; Borrajo, Daniel

doi:10.1016/j.eswa.2006.12.029

Cited by 106 publications

(58 citation statements)

References 18 publications

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“…Multiintegrated CBR approaches, besides those involving RBR/MBR, could be developed. For instance, ontologies could constitute an interesting candidate method that could be combined with CBR and another intelligent method in order to facilitate knowledge sharing and reuse among the integrated system components themselves [5] and among integrated systems. Such a combination could be useful in Web-based systems that need to share knowledge.…”

Section: Combinations Of Cbr With Multiple Intelligent Methodsmentioning

confidence: 99%

Combinations of case-based reasoning with other intelligent methods

Prentzas

Hatzilygeroudis

2009

HIS

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Abstract. Case-based reasoning is a popular approach used in intelligent systems. Whenever a new case has to be dealt with, the most similar cases are retrieved from the case base and their encompassed knowledge is exploited in the current situation. Combinations of case-based reasoning with other intelligent methods have been explored deriving effective knowledge representation schemes. Although some types of combinations have been mostly explored, other types have not been thoroughly investigated. In this paper, we briefly outline popular case-based reasoning combinations. More specifically, we focus on combinations of case-based reasoning with rulebased reasoning, soft computing and ontologies. We illustrate basic types of such combinations and discuss future directions.

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Section: Combinations Of Cbr With Multiple Intelligent Methodsmentioning

confidence: 99%

Combinations of case-based reasoning with other intelligent methods

Prentzas

Hatzilygeroudis

2009

HIS

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“…With reference to the recommendation strategy, recommender systems can be classified in three major types: content-based, collaborative and demographic approaches (Montaner et al, 2003), (Borràs et al, 2014). In collaborative filtering approaches, recommendations are made by relating users with similar preferences and suggesting items they like (Castillo et al, 2008;Lee et al, 2009). Several ratings are, thus, required from the users before the system gives useful recommendations.…”

Section: Ontology In Tourism Systemsmentioning

confidence: 99%

A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism

Frikha

Mhiri

Gargouri

2015

ADCAIJ

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“…Again, no public transportation was taken into account. Castillo et al [8] described a multiagent based system for planning tourist visits. Although they mentioned transportation, they did not integrate selection and routing nor give hints or details about the implementation or performance.…”

Section: State Of the Artmentioning

confidence: 99%

Personalized Tourist Route Generation

García

Arbelaitz

Linaza

et al. 2010

Current Trends in Web Engineering

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Abstract.When tourists are at a destination, they typically search for information in the Local Tourist Organizations. There, the staff determines the profile of the tourists and their restrictions. Combining this information with their up-to-date knowledge about the local attractions and public transportation, they suggest a personalized route for the tourist agenda. Finally, they fine tune up this route to better fit tourists' needs. We present an intelligent routing system to fulfil the same task. We divide this process in three steps: recommendation, route generation and route customization. We focus on the last two steps and analyze them. We model the tourist planning problem, integrating public transportation, as the Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) and we present an heuristic able to solve it on real-time. Finally, we show the prototype which generates and customizes routes in real-time.

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samap: An user-oriented adaptive system for planning tourist visits

Cited by 106 publications

References 18 publications

Combinations of case-based reasoning with other intelligent methods

Combinations of case-based reasoning with other intelligent methods

A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism

Personalized Tourist Route Generation

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