We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the ...

Social media data associated with geographic location and time information reflect people footprint in real world. Abundance of geo-referenced content represents a massive opportunity to understanding of human geographic mobility behaviors. Most trajectory mining research from geo-enabled social media data focus on spatial geometric features. Integrating trajectory analysis with semantic inform...

Semantic trajectory pattern mining is becoming more and more important with the rapidly growing volumes of semantically rich trajectory data. Extracting sequential patterns in semantic trajectories plays a key role in understanding semantic behaviour of human movement, which can widely be used in many applications such as location-based advertising, road capacity optimisation, and urban plannin...

The paper discusses some issues that arise from research on sign languages in the area of formal semantics. Sign languages provide a unique standpoint to investigate semantic phenomena like donkey anaphora, indexical reference shift, and tense. Moreover, they pose a challenge for semantic theories, since movement verbs display gradient properties (semi-continuous variations with semantic import...

INTRODUCTION We analyse a large sample of the Twitter activity that developed around the social movement 'Occupy Wall Street', to study the complex interactions between the human communication activity and the semantic content of a debate. METHODS We use a network approach based on the analysis of the bipartite graph @Users-#Hashtags and of its projections: the 'semantic network', whose nodes...

Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an ob...

Using real-time eye-movement measures, we asked how a fantastical discourse context competes with stored representations of semantic and world knowledge to influence children's and adults' moment-by-moment interpretation of a story. Seven-yearolds were less effective at bypassing stored semantic and world knowledge during real-time interpretation than adults. Nevertheless, an effect of discours...

There is an increasing number of rapidly growing repositories capturing the movement of people in spacetime. Movement trajectory compression becomes an obvious necessity for coping with such growing data volumes. This paper introduces Semantic Trajectory Compression (STC), which allows for substantially compressing trajectory data with acceptable information loss. STC exploits that human urban ...

In the light of rapidly growing repositories capturing the movement trajectories of people in spacetime, the need for trajectory compression becomes obvious. This paper argues for semantic trajectory compression (STC) as a means of substantially compressing the movement trajectories in an urban environment with acceptable information loss. STC exploits that human urban movement and its large–sc...

A brief account of the origins of the "outcomes" movement in education is given. It is concluded that there is no real difference between the objectives movement of yesterday and the "outcomes" movement of today. Differences between the approaches of Mager and the authors of The Taxonomy of Eductional Objectives are outlined. Some limitations of The Taxonomy from an engineering perspective are ...