A criteria based function for reconstructing low-sampling trajectories as a tool for analytics

Abstract: Mobile applications equipped with Global Positioning Systems have generated a huge quantity of location data with sampling uncertainty that must be handled and analyzed. Those location data can be ordered in time to represent trajectories of moving objects. The data warehouse approach based on spatio-temporal data can help on this task. For this reason, we address the problem of personalized reconstruction of low-sampling trajectories based on criteria over a graph for including criteria of movement as a dimension in a trajectory data warehouse solution to carry out analytical tasks over moving objects and the environment where they moveMaestrí

Social contextuality and conversational recommender systems

As people continue to become more involved in both creating and consuming information, new interactive methods of retrieval are being developed. In this thesis we examine conversational approaches to recommendation, that is, the act of suggesting items to users based on the system’s understanding of them. Conversational recommendation is a recent contribution to the task of information discovery. We propose a novel approach to conversation around recommendation, examining how it is improved to work with collaborative filtering, a common recommendation algorithm. In developing new ways to recommend information to people we also examine their methods of information seeking, exploring the role of conversational recommendation, using both interview and sensed brain signals. We also look at the implications of the wealth of social and sensed information now available and how it improves the task of accurate recommendation. By allowing systems to better understand the connections between users and how their social impact can be tracked we show improved recommendation accuracy. We look at the social information around recommendations, proposing a directed influence approach between socially connected individuals, for the purpose of weighting recommendations with the wisdom of influencers. We then look at the semantic relationships that might seem to indicate wisdom (i.e. authors on a book-ranking site) to see if the ``wisdom of the few'' can be traced back to those conventionally considered wise in the area. Finally we look at ``contextuality'' (the ability of sets of contextual sensors to accurately recommend items across groups of people) in recommendation, showing that different users have very different uses for context within recommendation. This thesis shows that conversational recommendation can be generalised to work well with collaborative filtering, that social influence contributes to recommendation accuracy, and that contextual factors should not be treated the same for each user

Managing the Paradox of Growth in Brand Communities Through Social Media

The commercial benefits of online brand communities are an important focus for marketers seeking deeper engagement with increasingly elusive consumers. Managing participation in these socially bound brand conversations challenges practitioners to balance authenticity towards the community against corporate goals. This is important as social media proliferation affords communities the capacity to reach a scale well beyond their offline equivalents and to operate independently of brands. While research has identified the important elements of engagement in brand communities, less is known about how strategies required to maximise relationships in these circumstances must change with growth. Using a case study approach, we examine how a rapidly growing firm and its community have managed the challenges of a maturing relationship. We find that, in time, the community becomes self-sustaining, and a new set of marketing management strategies is required to move engagement to the next level

Managing the Paradox of Growth in Brand Communities Through Social Media

The commercial benefits of online brand communities are an important focus for marketers seeking deeper engagement with increasingly elusive consumers. Managing participation in these socially bound brand conversations challenges practitioners to balance authenticity towards the community against corporate goals. This is important as social media proliferation affords communities the capacity to reach a scale well beyond their offline equivalents and to operate independently of brands. While research has identified the important elements of engagement in brand communities, less is known about how strategies required to maximise relationships in these circumstances must change with growth. Using a case study approach, we examine how a rapidly growing firm and its community have managed the challenges of a maturing relationship. We find that, in time, the community becomes self-sustaining, and a new set of marketing management strategies is required to move engagement to the next level

Shared Experiences in Personalized Route Planning

In this paper we discuss personalized planning (as opposed to personalized information retrieval) where instead of recommending atomic information assets to users, the goal is to construct composite plans that reflect the complex problem solving preferences of users within a particular domain