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Automatic categorization of videos in a Web-scale unconstrained collection such as YouTube is a challenging task. A key issue is how to build an effective training set in the presence of missing, sparse or noisy labels. We propose to achieve this by first manually creating a small labeled set and then extending it using additional sources such as related videos, searched videos, and text-based webpages...
Text detection in images is important for the retrieval of text information from digital graph, video databases and web sites. In this paper, a text detection method based on sparse representation classification with discrimination dictionaries is presented, which can detect text with different sizes, fonts and colors. The propose method detects edge information using Sobel operator and a sliding...
With the rapid developing of the network information, it seems to be quite important to provide a more reasonable text classification algorithm for learners. In this paper,we adopt a sensitivity method to modify the characteristic weight in the distance formula and put up with a cutting method of training sample database based on CURE algorithm and Tabu algorithm; then adopt CURE cluster algorithm...
With rapid development of Internet information, It is quite an important project for data mining that how to classify these large amounts of texts. In this paper, we propose an improved text classify cluster algorithm, while calculating similarity, we synthetically consider the relationship between keywords and eigenvector representation on base of term frequency statistics, thereby it lessens sensitivity...
Typically Web pages always contain a large amount of banner ads, navigation bars, and copyright notices etc. Such irrelevant information is not part of the main contents of the pages, they will seriously harm Web mining and searching. In this paper, we develop and evaluate a method that utilizes both the visual features and the semantic information to extract informative blocks. We first partition...
We present a higher-level visual representation, visual synset, for object categorization. The visual synset improves the traditional bag of words representation with better discrimination and invariance power. First, the approach strengthens the inter-class discrimination power by constructing an intermediate visual descriptor, delta visual phrase, from frequently co-occurring visual word-set with...
Peer-to-peer (P2P) networks have received more and more attention from researchers. P2P seems to be an interesting architectural paradigm for realizing large-scale information retrieval systems for its scalability, failure resilience and increased autonomy of nodes. This paper provides a novel peer-to-peer networks system that is based on information retrieval in a large-scale collection of texts,...
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