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Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep...
Detecting daily activities is helpful for health care and clinical medicine. In this paper, we present ActDetector, a smartwatch based application which detects 8 common daily activities, including sitting, walking, running, going upstairs, going downstairs, eating, driving and sitting in a vehicle. By leveraging the built-in sensors on smartwatch, a multi-level classification system is proposed which...
With the rapid development of B2C e-commerce and the popularity of online shopping, the Web storages huge number of product reviews comment by customers. Product reviews contain subjective feelings of customers who have used some products, more and more customers browse a large number of online reviews in order to know other customers word-of-mouth of product and service to make an informed choice...
Related research for sentiment analysis on Chinese microblog is aiming at analyzing the emotion of posters. This paper presents a content extension method that combines post with its' comments into a microblog conversation for sentiment analysis. A new convolutional auto encoder which can extract contextual sentiment information from microblog conversation of the post is proposed. Furthermore, a DBN...
This paper presents a DBN (deep belief nets) model and a multi-modality feature extraction method to extend features' dimensionalities of short text for Chinese micro blogging sentiment classification. Besides traditional features sets for document classification, comments for certain posts are also extracted as part of the micro blogging features according to the relationship between commenters and...
In this paper, Deep Belief Nets(DBN) model and Support Vector Machine(SVM) are used to mine the features hidden in social news, which can influence the emotions of men. Three feature selection methods for text modeling are used to build the input vectors of DBN, with the purpose of keeping the text information to the greatest extent. We take advantage of the deep features abstracted by DBN to build...
A DSP-based design method of finger vein recognition was proposed, and a finger vein authentication system FV-1 was developed. In this system, finger vein images were captured with infrared, and normalized through rotation correction, then they were segmented and thinned to wipe off useless segments. Finally, features on vein points were obtained and two finger vein images were matched in view of...
In the fields of Chinese natural language processing, recognizing simple and non-recursive base phrases is an important task for natural language processing applications, such as information processing and machine translation. Instead of rule-based model, we adopt the statistical machine learning method, newly proposed Latent semi-CRF model to solve the Chinese base phrase chunking problem. The Chinese...
In this paper, a support vector regression (SVR) based method is proposed to detect a geometric feature such as line equation, corner point and angle degree between straight lines in an image. Digital image with geometric figures is collected and transmitted into computer. Median filter is used to reduce noise in the original gray scale image. Then image contour with single-pixel width is obtained...
As an important image feature, a corner takes significant position in camera calibration, pattern recognition and image matching area. A large amount of image corner points are the intersecting points of the edges of polygons. A corner point extracting method based on support vector for regression (SVR) was proposed aimed at extracting intersecting points. First, a digital image of geometric figures...
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