[[abstract]]Predicting future events has great importance in many applications. Generally, rules with predicate events and consequent events are mined out, and then current events are matched with the predicate ones to predict the occurrence of consequent events. Many previous works focus on the rule mining problem; however, little emphasis has been attached to the problem of predicate events matching. As events often arrive in a stream, how to design an efficient and effective event predictor becomes challenging. In this paper, we give a clear definition of this problem and propose our own method. We develop an event filter and incrementally maintain parts of the matching results. By running a series of experiments, we show that our method...
Complex Event Recognition (CER) systems have become popular in the past two decades due to their abi...
In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple ...
Learning to predict rare events from sequences of events with categorical features is an important, ...
International audienceThis paper focuses on event prediction in an event sequence, where we aim at p...
Discovering frequent episodes over event sequences is an important data mining task. In many appli-c...
International audienceEvent prediction in sequence databases is an important and challenging data mi...
This paper address the problem of temporal pattern mining from multiple data streams containing temp...
Editor: John Shawe-Taylor We present a theoretical analysis for prediction algorithms based on assoc...
AbstractEpisode rules are event patterns mined from a single event sequence. They are mainly used to...
Events are real-world occurrences that unfold over space and time. Event mining from multimedia stre...
We study an open text mining problem-discovering conceptlevel event associations from a text stream....
Lion's share of process mining research focuses on the discovery of end-to-end process models descri...
Abstract. Discovering frequent patterns over event sequences is an important data mining problem. Ex...
International audienceLion’s share of process mining research focuses on the discovery of end-to-end...
More and more business activities are performed using information systems. These systems produce suc...
Complex Event Recognition (CER) systems have become popular in the past two decades due to their abi...
In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple ...
Learning to predict rare events from sequences of events with categorical features is an important, ...
International audienceThis paper focuses on event prediction in an event sequence, where we aim at p...
Discovering frequent episodes over event sequences is an important data mining task. In many appli-c...
International audienceEvent prediction in sequence databases is an important and challenging data mi...
This paper address the problem of temporal pattern mining from multiple data streams containing temp...
Editor: John Shawe-Taylor We present a theoretical analysis for prediction algorithms based on assoc...
AbstractEpisode rules are event patterns mined from a single event sequence. They are mainly used to...
Events are real-world occurrences that unfold over space and time. Event mining from multimedia stre...
We study an open text mining problem-discovering conceptlevel event associations from a text stream....
Lion's share of process mining research focuses on the discovery of end-to-end process models descri...
Abstract. Discovering frequent patterns over event sequences is an important data mining problem. Ex...
International audienceLion’s share of process mining research focuses on the discovery of end-to-end...
More and more business activities are performed using information systems. These systems produce suc...
Complex Event Recognition (CER) systems have become popular in the past two decades due to their abi...
In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple ...
Learning to predict rare events from sequences of events with categorical features is an important, ...