The hard and fuzzy c-meansalgorithms are widely used, effective tools for the problem of clustering n objects into (hard or fuzzy) groups of similar individuals when the data is available as object data, consisting o...
详细信息
The hard and fuzzy c-meansalgorithms are widely used, effective tools for the problem of clustering n objects into (hard or fuzzy) groups of similar individuals when the data is available as object data, consisting of a set of n feature vectors in RP. However, object data algorithms are not directly applicable when the n objects are implicitly described in terms of relational data, which consists of a set of n2 measurements of relations between each of the pairs of objects. New relational versions of the hard and fuzzy c-meansalgorithms are presented here for the case when the relational data can reasonably be viewed as some measure of distance. Some convergence properties of the algorithms are given along with a numerical example.
In several online services, automatic recommendation systems are needed to provide good experiences to users. There are four general recommendation types. One of them is the recommendation system based on the demograp...
详细信息
ISBN:
(纸本)9798350381566;9798350381559
In several online services, automatic recommendation systems are needed to provide good experiences to users. There are four general recommendation types. One of them is the recommendation system based on the demographics information. Usually, the data used in the recommendation system has a relation among itself. Therefore, we introduced a demographics recommendation system using the relation hardc-means (RHcM). In particular, the RHcM was applied to segment the data and create multi-prototypes. To make a recommendation, the k-NN was used. We tested our system on a bike sales transactions data set. We found that the average accuracy and Jaccard index for the 1st to 4th test data sets were 0.324 and 0.182, respectively.
For the video surveillance system nowadays, identifying the color of certain footage is paramount. Every time when it comes to a crime scene, the police will be able to extract useful information from the surveillance...
详细信息
ISBN:
(纸本)9781424465880
For the video surveillance system nowadays, identifying the color of certain footage is paramount. Every time when it comes to a crime scene, the police will be able to extract useful information from the surveillance cameras on the scene. Among that important information, "color" plays a major role and is not affected by the size, location, time or changes in shape of an object. Facts affecting the accuracy and efficiency of real-time color identification include the material and the parameter of camera lens, the parameters of infrared for the hardware part, and efficiency of software algorithms, accuracy and practical degree for the software part, and so forth. Although many methods using static analysis of color have been proposed, they cannot effectively solve the color recognition in the real-time video system. In this paper, we provide an approach using dynamicalgorithm for the real-time video system. The methodologies include the reduction of color dimension, color transformation, color classification and real-time color recognition. Lastly, we provide the methods for effectively improving both the efficiency and accuracy of a real-time surveillance system.
暂无评论