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A novel image recognition method based on the improved BDBN (Bilinear Deep Belief Network) model is presented, optimized with a MKL (Multiple Kernel Learning) strategy. All kernel functions in MKL are replaced by hierarchical feature representations, and the number of kernels is set to the number of layers of BDBN. The method is performed on the standard Caltech101 image dataset. The experiments show...
Fluid mechanics considers two frames of reference for an observer watching a flow field: Eulerian and Lagrangian. The former is the frame of reference traditionally used for flow analysis, and involves extracting particle trajectories based on a vector field. With this work, we explore the opportunities that arise when considering these trajectories from the Lagrangian frame of reference. Specifically,...
Automatic extraction of hyponymy relations between concepts in an ontology is significant for ontology learning and knowledge organization. In this paper, we propose a fusion approach of hyponymy relation extraction in patent domain, using Relative Decoration Degree (RDEG) to extract high precision relations, and then Association Rule (AR) to enrich those relations. We use Cilin to extend a word to...
Sentence similarity compute is an important part in question answering system based on frequency asking questions. The accuracy of the existing sentence similarity algorithm needs to be improved, so this paper presents a revised question similarity compute method. We combine the word order feature with vector space model algorithm. When we use the VSM to compute the question similarity, we propose...
In modern distributed measure and control systems, transmission and processing of real-time data requires each communication node to work in a unified time base in order to ensure the timeliness of data transmission. IEEE1588 precision clock synchronization protocol (PTP) is aimed to solve the high-precision clock synchronization, which supports software or hardware implementation. This paper analyzes...
Along with the increasing popularity of social web sites, users rely more on the trustworthiness information for many online activities among users. However, such social network data often suffers from severe data sparsity and aren't able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Nowadays, trust prediction is...
Query expansion methods based on search logs could improve the quality of search results to some extends. But when the search logs are sparse, this kind of query expansion methods will have poor quality of search results and are unable to meet the user's search request, etc. This paper presents the search log sparseness oriented query extension method. By introducing the determination rule of data...
As the consistency prediction of data view in information systems and actual data, data quality is of vital importance to decision making and the development of banking industry. In this paper, we firstly analyze the influence of data quality on the banking industry, and make researches on the current situation of banking industry data quality automated management. Then five evaluation dimensions...
Collaborative Filtering (CF) is one of the most successful recommendation techniques. Regardless of its success, it still suffers from some weaknesses such as data sparsity and user cold-start problems, resulting in poor recommendation accuracy and reduced coverage. Trust-based recommendation methods incorporate the additional information from the user's social trust network into collaborative filtering...
Selecting accurate and simple association rules that efficiently cover all data samples is very important in knowledge discovery. There are several measures to assess accuracy and relations in a rule. This poses a challenge for researchers to select effective measures. Combining different measures via multi-objective evolutionary algorithms is an effective method to select suitable association rules...
Along with the wide use of web application, XSS vulnerability has become one of the most common security problems and caused many serious losses. In this paper, on the basis of database query language technique, we put forward a static analysis method of XSS defect detection of java web application by analyzing data flow reversely. This method first converts the JSP file to a Servlet file, and then...
Demand Response(DR) is a common practice used by utility providers to regulate energy demand. It is used at periods of high demand to minimize the peak to average consumption ratio. Several methods have been proposed over the previous years on how to formulate and deal with the problem of excess demand. Following these methods automated systems for initiating and regulating demand response events...
Many important network security areas, such as Intrusion Detection System and Next-Generation Firewall, leverage Traffic Classification techniques to reveal application-level protocols. Machine Learning algorithms give us the ability to identify encrypted or complicated traffic. However, classification accuracies of Machine Learning algorithms are always facing challenges and doubts in practical usage...
Recommendation systems suggest useful information to the end users. They predict the information demands of online users and offer recommendations to facilitate their navigation. There are many approaches to construct such systems. Most of the recommendation systems use data mining techniques on the web access log or the database of the site and discover user's access patterns. Afterwards, the recommendation...
Grammar Induction (GI) is the problem of extracting hidden regularities and syntactic patterns in languages. Not only the manner of extraction is intricate but also the definition of meaningful patterns is a challenge. Alignment Based Learning (ABL) is one of the research endeavors targeting such challenges in GI. Our present research on applying ABL to POS sequences in English, Persian and Arabic...
Method of improving the safety of autonomous vehicles are diverse. In particular, Path Tracking phase which is the last step and important to operate an autonomous vehicle. Method of Path tacking are diverse. Kinematic and dynamic methods is typically methods. In this study, Among Kinematic method, Pure pursuit is used by using the path tracking. Commonly pure pursuit is used to path tracking of mobile...
Cross validation method has been widely used for estimation of perfomance of classifiers and statistical method. However, compared with other resampling methods, cross-validation has not yet theoretically investigated since the sampling scheme is based not only on stochasticity but also on set-based processing. This paper proposes a new framework for evaluation of cross-validation methods based on...
The imbalance data problem in classification is a significant research area and has attracted a lot attention in recent years. Rebalancing class distribution techniques such as over-sampling or under-sampling are the most common approaches to deal with this problem. This paper presents a new method so called Diversity and Separable Metrics in Over-Sampling Technique (DSMOTE) to handle the imbalanced...
Collaborative filtering (CF) is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it suffers from several inherent deficiencies such as data sparsity and cold start. To better show user preferences for the cold users additional information (e.g., trust) is often applied. We describe the stages based on which the ratings of an active...
Onset detection is one of the main issues towards self-paced BCIs that can be used outside research settings. For this reason, this paper suggests a potential solution for onset detection problem by discriminating between speech related events. In this study, overt, inhibited overt and covert states were tested to classify from idle state in an off-line setting. Autoregressive model coefficients were...
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