Luis Otávio Alvares

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The collection of moving object data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data in different application domains. Trajectory data are normally available as sample points, and do not carry semantic information, which is of fundamental importance for the(More)
Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which the background geographic information is integrated to(More)
Trajectory data play a fundamental role to an increasing number of applications, such as transportation management, urban planning and tourism. Trajectory data are normally available as sample points. However, for many applications, meaningful patterns cannot be extracted from sample points without considering the background geographic information. In this(More)
Existing works for semantic trajectory data analysis have focused on the intersection of trajectories with application important geographic information and the use of the speed to find interesting places. In this paper we present a novel approach to find interesting places in trajectories, considering the variation of the direction as the main aspect. The(More)
The constant increase of moving object data imposes the need for modeling, processing, and mining trajectories, in order to find and understand the patterns behind these data. Existing works have mainly focused on the geometric properties of trajectories, while the semantics and the background geographic information has rarely been addressed. We claim that(More)
Geographic data preprocessing is the most effort and time consuming step in spatial data mining. In order to facilitate geographic data preprocessing and increase the practice of spatial data mining, this paper presents Weka-GDPM, an interoperable module that supports automatic geographic data preprocessing for spatial data mining. GDPM is implemented into(More)
The huge amount of information on the Internet creates a problem for the users – information overload. For this reason, finding the worthwhile information is becoming a challenge. To aid users a new approach based on Recommender System. This type of system applies information filtering in order to recommend items to a user based on the user's profile and(More)
Enormous quantities of trajectory data are collected from many sources, as GPS devices and mobile phones, as sequences of points. These data can be used in many application domains such as traffic management, urban planing, tourism, and bird migration. However, in most applications a higher level of abstraction should be used instead of sample points. In(More)