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This paper describes the Personal Tour recommender system that helps customers to find best travel packages according to their preferences. Personal Tour is based on the paradigm of the Distributed Artificial Intelligence and a customer recommendation request is divided into partial recommendations that are handled by different agents. Experiments were run(More)
This paper presents an approach for knowledge discovery in texts extracted from the Web. Instead of analyzing words or attribute values, the approach is based on concepts, which are extracted from texts to be used as characteristics in the mining process. Statistical techniques are applied on concepts in order to find interesting patterns in concept(More)
This work presents a recommender system that helps travel agents in discovering options for customers , especially those who do not know where to go and what to do. The system analyzes textual messages exchanged between a travel agent and a customer through a private Web chat. Text mining techniques help discover interesting areas in the messages. After(More)
This paper presents a Text Mining approach for discovering knowledge in texts to later construct decision support systems. Text mining can take advantage of knowledge stored in textual documents, reducing the effort for knowledge acquisition. The approach consists in performing a mining process on concepts present in texts instead of working with words. The(More)
This paper presents how text-mining techniques can be used to analyze an enterprise's external environment searching for competitors, related products and services, marketing strategies and customers' opinions. A case study, using the UNCTAD Electronic Trading Opportunities (ETO) System, is presented. The ETO system enables " Trade Points " and(More)
This paper presents an approach that identifies Location Indicators related to geographical locations, by analyzing texts of news published in the Web. The goal is to semi-automatically create Gazetteers with the identified relations and then perform geo-referencing of news. Location Indicators include non-geographical entities that are dynamic and may(More)
This work investigates the use of keywords and classes to represent user's profiles in order to improve a content-based recommender system. The techniques were implemented and tested in a recommender system for a website that gathers commercial ads. Ads are posted by individuals and contain a title and a textual description. Profiles are created and(More)
In multi-agent recommender systems, agents are able to generate recommendations according to the preferences of the customer. However, in some domains, specific knowledge is required in order to compose a recommendation and this knowledge may be not available for the agent. In these cases, agents need to communicate with other agents in the community(More)