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Adaptive streaming improves user-perceived quality by altering the streaming bitrate depending on network conditions, trading reduced video bitrates for reduced stall times. Existing adaptation approaches, e.g., rate-based, buffer-based, either rely heavily on accurate bandwidth prediction or can be overly-conservative about video bitrates. In this work, we propose a reinforcement learning approach...
In this paper, we investigate the machine learning based strategies for dynamic channel selection in Cognitive Access Points (CogAPs) of WLANs. We employ Multi-layer Feedforward Neural Network (MFNN) models that utilize historical traffic information from network environment for learning the influence of spatio-temporal-spectral factors on the network and then predicting future traffic loads on each...
In this paper, we propose some machine learning techniques for the acquisition of subcategorization frames (SCFs) information from parsed corpora for Chinese. A smoothing algorithm is used in order to minimize mistake caused by falsely parsing. Our algorithm is based on Support Vector Machines to filter improper SCFs extracted from low quality corpora parsed by dependency parser which we show give...
This article makes further study on data needed by automatic construction for Chinese medicinal ontologypsila concept description architecture, reconstructs and uses recognized knowledge in Chinese medicinepsilas domain by theory and technology of NLP. Based on realizing Chinese medicine knowledge description architecturepsilas automatic construction and acquiring successfully, this article use expertspsila...
This article makes further study on data needed by automatic construction for Chinese medicine ontology' concept description architecture, reconstructs and uses recognized knowledge in Chinese medicine's domain by theory and technology of NLP. Based on realizing Chinese medicine knowledge description architecture's automatic construction and acquiring successfully , this article use experts' knowledge...
On the base of deep study of domain ontology's evolution's principle,gist,method and model , this paper reconstructs and uses such recognized ontology knowledge as professional thesaurus, professional dictionary and textbook and realizes knowledge collection and manipulation to build auto-learning system of depended text's ontology finally to set up automatic construction of domain ontology's concept...
The estimation of the block importance could be defined as a learning problem. First, a vision-based page segmentation algorithm is used to partition a Web page into semantic blocks. Then spatial features and content features are used to represent each block. Considering the difference of Web pages, an entropy-based method is adopted to analyze the individual contribution of each feature to the overall...
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