BIOMEDICAL TEXTS CAN BE TYPICALLY REPRESENTED BY FOUR RHETORICAL CATEGORIES: introduction, methods, results and discussion (IMRAD). Classifying sentences into these categories can benefit many other text-mining tasks. Although many studies have applied approaches to automatically classify sentences in MEDLINE abstracts into the IMRAD categories, few have explored the classification of sentences...

The growing number of unauthorized activities and various trends of networking technologies in telecommunication network have added heavy burdens to telecommunication performance management (PM) system. One-class-support vector machine (OCSVM) is introduced in this paper, to automatically detect network anomalies. Real telecommunication performance data are employed in this paper to investigate...

Trust can be used to measure our confidence that a secure system behaves as expected. We had previously proposed a vector model of trust [1]. In this work we address the problem of trust management using the vector model. We develop a new trust management engine which we call VTrust (from Vector Trust). The trust management engine stores and manages current as well as historical information abo...

Customer response is a crucial aspect of service business. The ability to accurately predict which customer profiles are productive has proven invaluable in customer relationship management. An area that has received little attention in the literature on direct marketing is the class imbalance problem (the very low response rate). We propose a customer response predictive model approach combini...

This paper presents a fast and robust algorithm to identify text in image or video frames with complex backgrounds and compression effects. The algorithm first extracts the candidate text line on the basis of edge analysis, baseline location and heuristic constraints. Support Vector Machine (SVM) is then used to identify text line from the candidates in edge-based distance map feature space. Ex...

In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformation of the original problem to a high-dimensional (possibly infinite) feature space in which a linear decision hyperplane is constructed that yields a nonlinear classifier in the input space. However, since the classif...

T his paper provides a methodology for detecting management fraud using basic financial data. The methodology is based on support vector machines. An important aspect therein is a kernel that increases the power of the learning machine by allowing an implicit and generally nonlinear mapping of points, usually into a higher dimensional feature space. A kernel specific to the domain of finance is...

background: dengue is amongst the most serious mosquito-borne infectious disease with hot spots in tropical and subtropical parts of the world. unfortunately, no licensed vaccine for the disease is currently available in medicine markets. the only option available is the management of dengue vector mosquito, aedes aegypti (diptera: culicidae). method: predatory potential of five odonate nymphs ...

Learning to predict signiicant events from sequences of data with categorical features is an important problem in many application areas. We focus on events for system management, and formulate the problem of prediction as a classiication problem. We perform co-occurrence analysis of events by means of Singular Value Decomposition (SVD) of the examples constructed from the data. This process is...

context arthropod-borne diseases are remaining as a major public health issue in the resource-constrained settings. mosquitoes are closely associated with mankind since time immemorial and play an important role in the transmission of many dreadful diseases like malaria, filariasis, japanese encephalitis, dengue and yellow fever. over the decades, vector control is an important element to minim...