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Presented paper deals with problems related to automatic recognition of expressive speech states. The analysis was performed using the Slovene part of the emotional speech corpus recorded under the international project Interface. The main focuses of presented emotional multi-level based feature extraction method are not the emotions itself but rather three expressive states: positive, negative and...
This study concentrated on real-time monitoring of a worker using wearable-sensor-based activity recognition. An inertial measurement unit was attached to both wrists of the worker and, by using acceleration and angle speed information, the activities performed by the worker were recognized. Online recognition was done using the sliding window method to divide the data into two-second intervals, and...
Extracting data from Web pages using wrappers is a fundamental problem arising in a large variety of applications of vast practical interests. There are two main issues relevant to Web data extraction, namely wrapper generation and wrapper maintenance. In this paper, we propose a novel approach to the problem of automatic wrapper maintenance. It is based on the truth that despite various page changes,...
With information technology developing rapidly, variety and quantity of image data is increasing fast. How to retrieve desired images among massive images storage is getting to be an urgent problem. In this paper, we established a Distributed Image Retrieval System (DIRS), in which images are retrieved in a content-based way, and the retrieval among massive image data storage is speeded up by utilizing...
When browsing news on the web, various emotions may be evoked in readers and furthermore cause different influence on their minds and life. We expect that emotional analysis and classification of text may provide good performance and significance to users surfing the Internet. Most previous research only focus on bi-emotion classification, that is, Positive and Negative, e.g., identifying whether...
Internet is becoming an increasingly important platform for ordinary life and work. It is expected that keyword extraction can help people quickly find hot spots on the web, since keywords in a document provide important information about the content of the document. In this paper, we propose to use text clustering method based on semi-supervised learning to get focuses of social topics in a large...
In order to improve detection efficiency of on-line web news stream, we propose a new method to accomplish detection task with window-adding, named entity recognition and suffix tree clustering. In our method, we make full use of informative elements of news stream(such as date, place, person and so on) to help detection process, and this method decreases text similarity computation greatly. Experimental...
Nowadays, many people suffer from negative moods like sadness or anxiety. As an effective tool to relieve such moods, music therapy is widely embraced. Furthermore, researchers try to use newly developed bio-feedback technologies like electroencephalograms (EEG) to measure the effects of music therapy since it can reflect people's emotion sensitively and objectively. In this paper, we design a mobile...
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