Alexios Kotsifakos

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Automatic music genre classification is a task that has attracted the interest of the music community for more than two decades. Music can be of high importance within the area of assistive technologies as it can be seen as an assistive technology with high therapeutic and educational functionality for children and adults with disabilities. Several(More)
Performing similarity search in large databases is a problem of particular interest in many communities, such as music, database, and data mining. Although several solutions have been proposed in the literature that perform well in many application domains, there is no best method to solve this kind of problem in a Query-By-Humming (QBH) application. In QBH(More)
We propose a novel subsequence matching framework that allows for gaps in both the query and target sequences, variable matching tolerance levels efficiently tuned for each query and target sequence , and also constrains the maximum match length. Using this framework, a space and time efficient dynamic programming method is developed: given a short query(More)
Sequences of event intervals appear in several application domains including sign language, sensor networks , medicine, human motion databases, and linguistics. Such sequences comprise events that occur at time intervals and are time stamped at their start and end time. In this paper, we propose a new method, called IBSM, for comparing such sequences. IBSM(More)
We present " Hum-a-song " , a system built for music retrieval, and particularly for the Query-By-Humming (QBH) application. According to QBH, the user is able to hum a part of a song that she recalls and would like to learn what this song is, or find other songs similar to it in a large music repository. We present a simple yet efficient approach that maps(More)
An important theoretical topic in assistive environments is reasoning about temporal patterns, that represent the sequential output of various sensors, and that can give us information about the health and activities of humans and the state of the environment. The recent growth in the quantity and quality of sensors for assistive environments has made it(More)
Similarity search in large sequence databases is a problem ubiquitous in a wide range of application domains, including searching biological sequences. In this paper we focus on protein and DNA data, and we propose a novel approximate method method for speeding up range queries under the edit distance. Our method works in a filter-and-refine manner, and its(More)
We present a subsequence matching framework that allows for gaps in both query and target sequences, employs variable matching tolerance efficiently tuned for each query and target sequence, and constrains the maximum matching range. Using this framework, a dynamic programming method is proposed, called SMBGT, that, given a short query sequence Q and a(More)