Search Results

The constantly expanding volume of legal information presents a growing challenge for legal professionals to efficiently handle their workload. COLIEE is an annual competition organized with four tasks about automated legal information processing, ...

Most machine learning models are static, but the world is dynamic, and increasing online deployment of learned models gives increasing urgency to the development of efficient and effective mechanisms to address learning in the context of non-stationary ...

Nowadays, with the advance of technology, many applications generate huge amounts of data streams at very high speed. Examples include network traffic, web click streams, video surveillance, and sensor networks. Data stream mining has become a hot ...

A streaming time series is a continuous and unbounded group of chronological observations that are found in many scientific and business applications. Motifs that are frequent subsequences are highly representative for the time series and play an ...

We present methods to predict and validate home and work places of anonymized users using their mobile network data. Knowledge of home and work place of a user is essential in order to find his (and overall population) mobility profiles. There are many ...

Knowledge about population distribution of planning areas helps in making urban development decisions. Two important criteria are: "where do people live?" and "where do they work?" In this paper we propose methods to find home and workplaces from mobile ...

The nature of data streams requires classification algorithms to be real-time, efficient, and able to cope with high-dimensional data that are continuously arriving. It is a known fact that in high-dimensional datasets, not all features are critical for ...

Conventional stream mining algorithms focus on single and stand-alone mining tasks. Given the single-pass nature of data streams, it makes sense to maximize throughput by performing multiple complementary mining tasks concurrently. We investigate the ...

Computing scalar products amongst private vectors in a secure manner is a frequent operation in privacy-preserving data mining algorithms, especially when data is vertically partitioned on many parties. Existing secure scalar product protocols based on ...