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Providing high quality recommendations is significant for e-commerce systems to assist users in making effective selection decisions from a plethora of choices. Collaborative filtering (CF) is one of the most well-known and successful techniques to generate recommendations. However, CF suffers from an inherent issue that does not think over the auxiliary information such as item content information...
The emergence of network television (IPTV) has heavily promoted development of the technology and prosperity of the market in the TV industry. In order to win in the fierce competition, IPTV content providers need to be sure to provide users with interesting service, and operators also need to ensure quality of service transmission so that they can improve users quality of experience (QoE). How to...
IPTV is an increasingly important service for telecom operators. Service providers have to repair IPTV faults quickly in order to provide high quality service. It will be very helpful if faults can be predicted. Considering this situation, we combine status data from the set top box with the data of customer trouble tickets and then build a prediction system with improved AdaBoost to predict faults...
Recently, every enterprise generates large volumes of high dimensional data on a regular basis. Complex data mining and analysis techniques are used to feasibly analyse this data. Feature selection aids in this by providing a reduced representation of this data while maintaining integrity. We propose a graph-based feature selection algorithm utilizing feature intercorrelation to construct a weighted...
Nowadays large portion of web-based businesses, research projects, and scientist use recommendation systems to help their business to thrive & flourish. Standard recommendation system utilises either user CF, item CF or content based recommendation system, these furthermore confront issues like item cold start, user cold start and real-time prediction problem. In the perspective of these challenges,...
In Mandarin language speaking, some consonant and vowel pairs are hard to be distinguished and pronounced clearly even for some native speakers. This study investigates the signal distance between consonants compared in pairs from the signal processing point of view to reveal the correlation of signal distance and consonant pronunciation. Some popular speech quality objective measures are innovatively...
In this paper, we propose a signal-centric medium access control scheme that simultaneously exploits spatial and temporal correlations among sensing results for machine-to-machine communications. To model sensing results with spatial and temporal correlations, we propose using a vector autoregressive process. To minimize the overall prediction error, we propose using the space- time predictive polling...
HEVC employs a quad-tree based Coding Unit (CU) structure to achieve a significant improvement in coding efficiency compared with previous standards. However, the computational complexity is greatly increased. We proposed a fast mode decision algorithm to reduce intra coding complexity. Firstly, an initial candidate list of intra modes is constructed for each Prediction Unit (PU). The prediction mode...
Subjective experimental results are widely used as the ground truth in objective Image Quality Assessment (IQA). Specifically, Pairwise Comparison method has superiority over Mean Opinion Scores (MOS), but there is a problem when measuring the consistency between subjective pairwise comparisons and objective quality predictions. In this paper, we first analyze the existing problem of current evaluation...
This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor...
35 intra-prediction modes in High Efficiency VideoCoding (HEVC) make the prediction image more accurate andsignificantly improve the coding image quality, but numerousintra-prediction modes results in a remarkable rise incomputational complexity compared with H.264.In order toreduce computational complexity, a low-complexity HEVC intracomputation method that utilizes image textural featureinformation...
Accurate demand forecasting could reduce the uncertainty of inventory and provide theoretical basis for strategic decisions. Without the accurate prediction of actual market demand, there will be a supply shortage or surplus, which influences the enterprise's inventory level and costs of operation. Product substitution is an important factor which affects the precision of demand forecasting. It could...
To cope with the severe energy challenges caused by incessant mobile network expansion, the multi-RAT cooperation energy-saving system (MCES) was developed to effectively improve the energy efficiency of mobile networks. MCES interacts with the radio access network in a real-time manner and can support multiple vendors' 2G/3G/4G RAN equipment. Therefore, amount of data have ushered in the application...
We investigate the problem of reducing the number of branch mispredictions for a task such that its WCET (Worst-Case Execution Time) is minimized, and propose a novel branch correlation-based, hybrid branch prediction approach. Our approach consists of a static profile-based branch correlation analyzer and a dynamic branch predictor. The static profile-based branch correlation analyzer uses profiling...
To improve the prediction precision of residential property, the paper brings up a mixed optimizing model based on IPSO-BPNN. The model has adopted gray correlation theory to optimized the the index that influences price and use IPSO to optimize the definition of original weights and threshold value. We take the real estate market in Changsha as an example. The result shows that the speed of convergence...
An enormous increase in the number of internet users which will tend to rise further, cluster-based web servers (CBWS) are experiencing a dramatic increase in web traffic. Round-robin load-balancing algorithm (RLBA), is one of the most widely used for distributing loads among the web servers due to its simplicity. However, in the case of non-uniform web traffic, RLBA load distribution is inefficient...
Because the English and Castilian have marked acoustic and phonetic differences, this paper shows the study of the effectiveness of different algorithms VAD (Voice Activity Detection) literature, applied to the Castilian, especially riplatense. This article is intended to publicize the results achieved to date. In the first part of the document briefly explained the three implemented methods, namely...
Feature selection is the most important preprocessing step for classification of high dimensional data. It reduces the load of computational cost and prediction time on classification algorithm by selecting only the salient features from the data set for learning. The main challenges while applying feature selection on high dimensional data (HDD) are: handling the relevancy, redundancy and correlation...
Collaborative filtering provides recommendations based on the behavior of each user combined with behavior of users with similar interests. Recommender systems are becoming widespread, helping people choose movies, books, and things to buy. In this study, we examine the use of Biclustering ARTMAP to build a collaborative filtering recommendation system. We introduce a novel modification to how the...
Abnormal joint moments during gait are validated predictors of knee pain in osteoarthritis. Calculation of moments necessitates measurement of forces and moment arms about joints during walking. Dynamically changing moment arms can be calculated from motion trackers either optically or with wireless inertia sensing units, but the measurement of forces is more problematic. Either the patient has to...
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