Current Issue : October - December Volume : 2012 Issue Number : 4 Articles : 6 Articles
The language tools offered in common word processors use dictionaries and simple grammatical rules. They cannot detect errors\r\nsuch as a wrong preposition, interchanged words, or typos that result in a dictionary word. However, by comparing the userââ?¬â?¢s text\r\nto a large repository, it is possible to detect many of these errors and also to suggest alternatives. By looking at full sentences, it is\r\noften possible to get the correct context. This is important in detecting errors and in order to offer valuable suggestions. These ideas\r\nhave been implemented in a prototype system.We present examples in English and Norwegian, but the method, that of following\r\na ââ?¬Å?majority vote,ââ?¬Â can be applied to any written language....
DBSCAN is a base algorithm for density-based clustering. It can find out the clusters of different shapes and sizes from a large\r\namount of data, which is containing noise and outliers. However, it is fail to handle the local density variation that exists within\r\nthe cluster. Thus, a good clustering method should allow a significant density variation within the cluster because, if we go for\r\nhomogeneous clustering, a large number of smaller unimportant clusters may be generated. In this paper, an enhancement of\r\nDBSCAN algorithm is proposed, which detects the clusters of different shapes and sizes that differ in local density. Our proposed\r\nmethod VMDBSCAN first finds out the ââ?¬Å?coreââ?¬Â of each clusterââ?¬â?clusters generated after applying DBSCAN. Then, it ââ?¬Å?vibratesââ?¬Â\r\npoints toward the cluster that has the maximum influence on these points. Therefore, our proposed method can find the correct\r\nnumber of clusters....
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the point of view of its learning\r\ncapabilities. Very accurate Learning Curves are obtained, using high-performance computing, and extrapolations of the projected\r\nperformance of the system under different conditions are provided. Our experiments confirm existing and mostly unpublished\r\nbeliefs about the learning capabilities of statistical machine translation systems. We also provide insight into the way statistical\r\nmachine translation learns from data, including the respective influence of translation and language models, the impact of\r\nphrase length on performance, and various unlearning and perturbation analyses. Our results support and illustrate the fact\r\nthat performance improves by a constant amount for each doubling of the data, across different language pairs, and different\r\nsystems. This fundamental limitation seems to be a direct consequence of Zipf law governing textual data. Although the rate of\r\nimprovement may depend on both the data and the estimation method, it is unlikely that the general shape of the learning curve\r\nwill change without major changes in the modeling and inference phases. Possible research directions that address this issue include\r\nthe integration of linguistic rules or the development of active learning procedures....
We present a system which combines interactive visual analysis and recommender systems to support insight generation for the\r\nuser. Our approach combines a stacked graph visualization with a content-based recommender algorithm, where promising views\r\ncan be revealed to the user for further investigation. By exploiting both the current user navigational data and view properties, the\r\nsystem allows the user to focus on visual space in which she or he is interested. After testing with more than 30 users, we analyze\r\nthe results and show that accurate user profiles can be generated based on user behavior and view property data....
This paper proposes improvement in clonal algorithm by introducing quantum bits in the development of population and quantum inspired clonal algorithm a novel optimization approach for the solution of Economic Load Dispatch. The approach utilizes clonal selection principle and evolutionary approach wherein cloning of antibodies is performed and followed by hyper mutation. The developed AIS technique uses the total operating cost as objective function and it is represented by affinity measure. The proposed algorithm is tested with multiple units and multiple load demand conditions and results are compared with other prevalent methods like particle swarm optimization, lambda iteration, genetic algorithm and clonal algorithm. . The results divulge that the method is easy to implement, fast convergent and applicable for the solution of complex ELD problem....
A qualia exploitation of sensor technology (QUEST) motivated architecture using algorithm fusion and adaptive feedback loops\r\nfor face recognition for hyperspectral imagery (HSI) is presented. QUEST seeks to develop a general purpose computational\r\nintelligence system that captures the beneficial engineering aspects of qualia-based solutions. Qualia-based approaches are\r\nconstructed from subjective representations and have the ability to detect, distinguish, and characterize entities in the environment\r\nAdaptive feedback loops are implemented that enhance performance by reducing candidate subjects in the gallery and by injecting\r\nadditional probe images during the matching process. The architecture presented provides a framework for exploring more\r\nadvanced integration strategies beyond those presented. Algorithmic results and performance improvements are presented as\r\nspatial, spectral, and temporal effects are utilized; additionally, a Matlab-based graphical user interface (GUI) is developed to aid\r\nprocessing, track performance, and to display results....
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