In this paper, we present a scalable implementation of a topic modeling (Adaptive Link-IPLSA) based method for online event analysis, which summarize the gist of massive amount of changing tweets and enable users to e...
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Recently, l1-graph was proposed as a new graph construction procedure. Compared with the kNN-graph and Ε-graph, l1-graph possesses three advantages: robustness to data noise, sparsity and datum-adaptive neighborhood ...
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Cross-media is the outstanding characteristics of the age of big data with large scale and complicated processing task. This article presents 5 issues and briefly summarizes the research progress of cross-media knowle...
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Cross-media is the outstanding characteristics of the age of big data with large scale and complicated processing task. This article presents 5 issues and briefly summarizes the research progress of cross-media knowledge discovery. Furthermore, we propose a framework for cross-media semantic understanding which contains discriminative modeling, generative modeling and cognitive modeling. In cognitive modeling, a new model entitled CAM is proposed which is suitable for cross-media semantic understanding. Moreover, a Cross-Media intelligent Retrieval System (CMIRS) will be illustrated. In the final, the research directions and problems encountered are presented.
In this paper, we present a novel reversible data hiding method based on principal component analysis (PCA). Firstly, we generate a reference sub-sampled image and divide it into blocks. Secondly, according to the tex...
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In this paper, we present a novel reversible data hiding method based on principal component analysis (PCA). Firstly, we generate a reference sub-sampled image and divide it into blocks. Secondly, according to the texture information of each image blocks determined by PCA, the sequence of data embedding is obtained. Since the sequence is representative of image block texture from smooth to rich, secret data can be firstly embedded into smooth blocks adaptively in order to avoid large distortion. Finally, we modify the difference histogram between image blocks which exploits the high spatial correlation inherent in neighboring pixels to achieve high embedding capacity and good imperceptibility. Since the texture information is considered adequately, experimental results demonstrate that the performance of the proposed method outperforms several state-of-the-art methods.
An image retrieval algorithm based on the GHM multiwavelets texture and spatial features is proposed. The integrated multiwavelets quantization map is designed creatively that can describe the important visual informa...
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Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorith...
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We prove that Fv(3,5;6) = 16, which solves the smallest open case of vertex Folkman numbers of the form Fv(3,k;k + 1). The proof uses computer algorithms.
We prove that Fv(3,5;6) = 16, which solves the smallest open case of vertex Folkman numbers of the form Fv(3,k;k + 1). The proof uses computer algorithms.
For the problems of extracting question trunks and focus extraction completely by conventional dependency syntax parsing, this paper presents a method of question trunks and focus extraction oriented to question depen...
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For the problems of extracting question trunks and focus extraction completely by conventional dependency syntax parsing, this paper presents a method of question trunks and focus extraction oriented to question dependency syntax conversion with the characteristics of the questions. The method defines a number of combining rules of question dependency relations. According to the rules, we do merger, conversion and removal to parts component of question syntax, and extract the question trunks and focus based on question dependency syntactic structure. The experimental results show that the proposed method of question trunks and focus extraction based on dependency syntax conversion achieved good results.
We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrase-based model and the tree-to-string model, to combine the merits of the two models. With th...
ISBN:
(纸本)9781622761715
We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrase-based model and the tree-to-string model, to combine the merits of the two models. With the help of shallow parsing, our model learns rules consisting of words and chunks and meanwhile introduce syntax cohesion. Under the weighed synchronous context-free grammar defined by these rules, our model searches for the best translation derivation and yields target translation simultaneously. Our experiments show that our model significantly outperforms the hierarchical phrase-based model and the tree-to-string model on English-Chinese Translation tasks.
r the problem that many different classification of questions and answers and users changing from one interest to another,we propose a personalized user model based on multi-kernel support for vector data domain descr...
r the problem that many different classification of questions and answers and users changing from one interest to another,we propose a personalized user model based on multi-kernel support for vector data domain description (MSVDD).
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