With tags widely used in organizing and searching contents in massive data era,how to automatically generate appropriate tags of resource for users became a hot issue on social networks *** recommendation for text res...
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ISBN:
(纸本)9781509036202
With tags widely used in organizing and searching contents in massive data era,how to automatically generate appropriate tags of resource for users became a hot issue on social networks *** recommendation for text resource can be modeled as a keyword extraction problem,hence topic modeling such as LDA which extracts latent semantic topics from text is suitable for tag ***,latent topics are too coarse-grained to describe ***,LDA trains corpus globally without considering context ***,topics generated are difficult to be quantifiably *** problems lead to the poor quality of tag recommendation in topic model based *** this paper,we propose topic representation method,which introduces embedding semantic representation into topic *** results of evaluation on real social networks show that the proposed method improves the quality of tag recommendation for Chinese text resource,when comparing with traditional LDA-based method,which demonstrates the effectiveness of modifying topic modeling.
Medical synonym identification has been an important part of medical natural language processing(NLP).However,in the field of Chinese medical synonym identification,there are problems like low precision and low recall...
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ISBN:
(纸本)9781509036202
Medical synonym identification has been an important part of medical natural language processing(NLP).However,in the field of Chinese medical synonym identification,there are problems like low precision and low recall *** solve the problem,in this paper,we propose a method for identifying Chinese medical *** first selected 13 features including Chinese and English *** we studied the synonym identification results of each feature alone and different combinations of the *** the comparison among identification results,we present an optimal combination of features for Chinese medical synonym *** show that our selected features have achieved 97.37% precision rate,96.00% recall rate and 97.33% F1 score.
To solve the recognition of road sign with an intelligent vehicle in vision-based navigation, road sign extraction and matching techniques required in outdoor scene was proposed in this paper. The method of the improv...
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To solve the recognition of road sign with an intelligent vehicle in vision-based navigation, road sign extraction and matching techniques required in outdoor scene was proposed in this paper. The method of the improved curvature based on feature extraction and binary description took the advantage of reasonable features distribution to overcome the problems of traditional features uneven distribution. Binary description method was represented to solve the real-time problem of feature matching. Through the validity and real-time performance of different algorithms are compared by experiments and indicate that the method can not only overcome negative influences from the disturb of non-targets, while spending on average only 46 ms processing each frame, but also meet the requirements of robustness, real-time, and accuracy.
Considering the difficulty of fruit and vegetable images with uneven illumination and uncontrolled backgrounds, this paper proposed an image preprocess algorithm based on visual subject detection. Firstly, we can use ...
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Considering the difficulty of fruit and vegetable images with uneven illumination and uncontrolled backgrounds, this paper proposed an image preprocess algorithm based on visual subject detection. Firstly, we can use manifold ranking to significance test and to acquire significance images, then use gradient images and position weighting to get cutting images, finally adjust the image brightness and remove image noise to complete the image *** experiment results demonstrated the robustness and real-time of the proposed algorithm which can segment images accurately and the accuracy is higher than 91%.
It is a tough task for teachers to answer all questions from students effectively and *** this paper,we design and implements an intelligent question answering system using Natural Language Processing,template classif...
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It is a tough task for teachers to answer all questions from students effectively and *** this paper,we design and implements an intelligent question answering system using Natural Language Processing,template classification,support vector *** system also calculates the similarity between the question and answer pairs by cosine similarity algorithm,and returns the most similar *** the user is not satisfied with the answer,the system will write the question into the public section to fall back on other *** answer will be evaluated and added to the QA base if it is passed with the corresponding *** that the questions and answers in the QA base continue to *** use the QA base of a network forum as the basic library to carry out the *** implementation and experimental results indicate that the proposed approach is achievable.
With the rapid development of Internet,Internet traffic and end hosts continue to grow in *** behavior analysis for a large-scale network is becoming more and more *** address these challenges,this paper proposes an I...
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With the rapid development of Internet,Internet traffic and end hosts continue to grow in *** behavior analysis for a large-scale network is becoming more and more *** address these challenges,this paper proposes an Internet traffic analysis approach based on community detection to discover community consisted of end hosts with similar traffic behavior in a large campus ***,we use only the IP-to-IP information without packet payloads to model the similarity of end hosts in campus *** the similarity graph which represent the social behavior similarity of all end hosts is ***,we leverage label Propagation algorithm to discover end hosts community on the similarity *** satisfy demands for the scalable analysis of evergrowing Internet traffic data,a Spark-based Internet traffic analysis system is developed,including implementing the above *** experimental results based on real campus network traffic show the benefits of the proposed approach in analyzing traffic behavior of a large-scale network on host community level and detecting potential anomalous traffic *** proposed approach reduces the complexity of analyzing the traffic behavior of a large network compare with analyzing individual *** addition,the experimental results also demonstrate the Spark-based Internet traffic analysis system can analyze Internet traffic efficiently.
Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank repr...
Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.
This paper presents a novel but simple biometric image feature representation method, called exploring deep gradient information (DGI). DGI first captures the local structure of an image by computing the histogram of ...
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This paper presents a novel but simple biometric image feature representation method, called exploring deep gradient information (DGI). DGI first captures the local structure of an image by computing the histogram of gradient orientation of each macro-pixel (local patch around the reference pixel). Thus, one image can be decomposed into L sub-images (sub-orientation images) according to the gradient information of each macro-pixel since there are L bins in the local histogram. To enrich the gradient information, we also consider the gradient orientation and magnitude of original image as sub-images. For each sub-image, histogram of oriented gradient (HOG) is used to further explore the gradient orientation information. All HOG features are concatenated into one augmented super-vector. Finally, fisher linear discriminate analysis (FLDA) is applied to obtain the low-dimensional and discriminative feature vector. We evaluated the proposed method on the real-world face image datasets NUST-RWFR, Pubfig and LFW, the PolyU Finger-Knuckle-Print database and the PolyU Palmprint database. Experimental results clearly demonstrate the effectiveness of the proposed DGI compared with state-of-the-art algorithms, e.g., SIFT, HOG, LBP, POEM, LARK and IDLS.
The e-government system plays a prominent part in government's office work, however, in the development process, there exist some problems currently, such as repeated development of common functions but hard to sa...
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The e-government system plays a prominent part in government's office work, however, in the development process, there exist some problems currently, such as repeated development of common functions but hard to satisfy various personalized needs, independence of different systems which makes information difficult to share. These problems have seriously hindered development progress, increased development cost, and may result in information isolated islands. To solve these problems, this paper proposes an e-government oriented BPM OA platform, and introduces its design and implementation process. To achieve rapid development, by analysis and abstraction, we extract main features of common e-government systems and make them into configurable functions. The powerful form builder, the explicit authority management method and the BPMN 2.0 based workflow engine can significantly simplify the development and deployment process, promote the inter-system information exchange, and improve development efficiency.
Recent years,an amount of tourism micro-blog comments on the Internet have become an important source of information for potential customers and to improve the service quality. These micro-blog comments do help to res...
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Recent years,an amount of tourism micro-blog comments on the Internet have become an important source of information for potential customers and to improve the service quality. These micro-blog comments do help to research tourism resources or services before making decisions. Thus,sentiment analysis of tourism micro-blog comments has become a hot issue in the field of natural language processing and text mining. We designed a system called SASTMC by using web crawler,Chinese words segmentation,emotion words dictionary and an improved TF-IDF algorithm. It enhances expression ability of sentiment information of text words. Experiments on Sina micro-blog comments datasets demonstrate that our method can do the task well.
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