Within the SemEval-2013 evaluation exercise, the TempEval-3 shared task aims to advance research on temporal information processing. It follows on from TempEval-1 and -2, with: a three-part structure covering temporal expression, event, and temporal relation extraction; a larger dataset; and new single measures to rank systems – in each task and in general. In this paper, we describe the partic...

Mining spatial association rules is one of the most important branches in the field of Spatial Data Mining (SDM). Because of the complexity of spatial data, a traditional method in extracting spatial association rules is to transform spatial database into general transaction database. The Apriori algorithm is one of the most commonly used methods in mining association rules at present. But a sh...

Web APIs enjoy a significant increase in popularity and usage in the last decade. They have become the core technology for exposing functionalities and data. Nevertheless, due to the lack of semantic Web API descriptions their discovery, sharing, integration, and assessment of their quality and consumption is limited. In this paper, we present the Linked Web APIs dataset, an RDF dataset with se...

Restricted Boltzmann Machines (RBMs) are generative models which can learn useful representations from samples of a dataset in an unsupervised fashion. They have been widely employed as an unsupervised pre-training method in machine learning. RBMs have been modified to model time series in two main ways: The Temporal RBM stacks a number of RBMs laterally and introduces temporal dependencies bet...

A temporal graph is a data structure, consisting of nodes and edges in which the edges are associated with time labels. To analyze the temporal graph, the first step is to find a proper graph dataset/benchmark. While many temporal graph datasets exist online, none could be found that used the interval labels in which each edge is associated with a starting and ending time. Therefore we create a...

Dengue infection is an epidemic disease typically found in tropical region. Nowadays, the experts need to know the set of features on dengue infection in order to correctly classify the patients since these classes require different treatment. Our temporal dataset consists of clinical data and laboratory data. The data was collected from the first visit of patient until the date of discharge. W...

This paper reports on the Event StoryLine Corpus (ESC) v0.9, a new benchmark dataset for the temporal and causal relation detection. By developing this dataset, we also introduce a new task, the StoryLine Extraction from news data, which aims at extracting and classifying events relevant for stories, from across news documents spread in time and clustered around a single seminal event or topic....

In this paper, we propose a novel feature type to recognize human actions from video data. By combining the benefit of Volume Local Binary Patterns and Optical Flow, a simple and efficient descriptor is constructed. Motion Binary Patterns (MBP) are computed in spatio-temporal domain while static object appearances as well as motion information are gathered. Histograms are used to learn a Random...

In this article, we present an experimental end user application to query DeRiVE 2011 challenge dataset in an innovative and intuitive manner. After enriching the dataset with external sources of information, it is indexed in a way that enables users to submit queries combining keywords, location and temporal anchor, in a single search field. The goal is to ease event retrieval providing a simp...