23948133
Building Domain Ontology Based on Web Data and Generic Ontology
The automatic or semi-automatic construction of ontology has become a research topic of interest in recent years. This paper describes a mechanism for constructing domain specific ontologies automatically based on web data and generic ontology. Firstly, we employ the hierarchical agglomerative clustering(HAC) algorithm, clustering web pages hierarchically and resulting in a binary tree. Then an algorithm is proposed, which selectd from the binary tree the significative nodes as topics implying concepts of domain interests. Lastly, the Chinese generic ontology, HowNet, is introduced to evolve the topics (together with their hierarchical structures) into domain ontology. We experiment our method in the field of computer hardware based on web pages collected from Chinese BtoC web sites. An in-depth discussion on the experiment results is also given.
36918365
C3: A New Learning Scheme to Improve Classification of Rare Category Emails
This paper proposes C3, a new learning scheme to improve classification performance of rare category emails in the early stage of incremental learning. C3 consists of three components: the chief-learner, the co-learners and the combiner. The chief-learner is an ordinary learning model with an incremental learning capability. The chief-learner performs well on categories trained with sufficient samples but badly on rare categories trained with insufficient samples. The co-learners that are focused on the rare categories are used to compensate for the weakness of the chief-learner in classifying new samples of the rare categories. The combiner combines the outputs of both the chief-learner and the co-learner to make a finial classification. The chief-learner is updated incrementally with all the new samples overtime and the co-learners are updated with new samples from rare categories only. After the chief-learner has gained sufficient knowledge about the rare categories, the co-learners become unnecessary and are removed. The experiments on customer emails from an e-commerce company have shown that the C3 model outperformed the Naive Bayes model on classifying the emails of rare categories in the early stage of incremental learning.
13356041
Research on Distributed Data Mining Technology Based on Grid
Distributed data mining (DDM) techniques have become necessary for large and multi-scenario datasets requiring resources, which are heterogeneous and distributed. In this paper, we focused on distributed data mining based in grid. We have discussed and analyzed a new framework based on grid environments to execute new distributed data mining techniques on very large and distributed heterogeneous datasets. The architecture and motivation for the design have been presented. We pointed out that distributed data mining technology can offer a better solution since they are designed to work in a distributed environment by paying careful attention to the computing and communication resources.
15560929
UNDER DEVELOPMENTUCD in Chinese IT enterprises
A zoom lens system includes a first lens unit having a negative optical power, located closer to an object side, and a second lens unit having a positive optical power, located farther from the object side. Zooming is accomplished by varying the spacing between the first and second lens units. The surface of at least one lens element in the two lens units is a diffractive optical surface. At least one surface of the lens element is an aspherical surface.
15131459
An Ant Colony Optimization Algorithm for Learning Classification Rules
Ant colony optimization (ACO) algorithm has been applied to data mining recently. Aiming at Ant Miner, a classification rule learning algorithm based on ACO, this paper presents an enhanced Ant Miner, which includes two main contributions. Firstly, a rule punishing operator is employed to reduce the number of rules and the number of conditions. Secondly, an adaptive state transition rule and a mutation operator are applied to the algorithm to speed up the convergence rate. The results of experiments on some data sets demonstrate that the enhanced Ant-Miner can quickly discover better classification rules which have roughly competitive predicative accuracy and short rules
17772901
Interference Temperature Estimation Based on the Detection and Estimation of Angles of Arrival of Multiple Wide-Band Sources in Cognitive Radio Sensor Networks
Majority of evaluation methods on interference temperature algorithms are based on the assumption that either the interference signals or the user’s signals are no directions. This is a mathematical constraint that is not satisfied in many applications. In fact, without consideration the signal directions increase estimation interference temperature, that is, reduce the frequency utilizing chance for users. In this paper, we consider situations where the interference signals and user’s signals have directions in cognitive radio sensor networks. We propose an algorithm that estimates the interference temperature of this model using a generalization of the DOA¿direction of arrival algorithm. From this, we find the interference temperature and show that it does become smaller. We compare our method to the conventional (without considering directions) algorithm. The simulation studies show that the new method outperforms the conventional algorithm by reducing the estimation interference temperature and improving the frequency spectrum efficiency.
8279850
Analysis and Simulation Protocols Based on Slotted ALOHA for Plastic Optical Fiber Network
In this paper a novel multipriority reservation protocols for plastic optical fiber network is proposed. In conventional OCDMA system only allows finite units to transmit and access simultaneously according to the number of channels which be restricted by BER. To resolve this problem, a novel protocol based on slotted ALOHA is proposed in this paper. By using the reservation scheme and a distributed arbitration algorithm, channel collision and destination conflict can be avoided. The protocol can efficiently support the transmission of multimedia messages that require the different time-delay. The network throughput and average delay has been investigated by numerical analysis and simulation experiments. It is showed that the multipriority reservation protocol in this POF network is valid and efficient.