In this article, a brand-new information retrieval model based on Agent technology is proposed, which is to counteract some significant deficiencies existing in current information retrieval systems, such as resource ...
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In this article, a brand-new information retrieval model based on Agent technology is proposed, which is to counteract some significant deficiencies existing in current information retrieval systems, such as resource consuming much, information updating delayed and so on. The main idea of this model is to apply Agent technology into the information retrieval system in order to provide users a information retrieval model of new pattern, which could update on time, save resource through distributing the information retrieval task among clients, retrieval severs and information owners. And MWRA (Multi-weight Ranking Algorithm) is also proposed in this article to improve the ranking capability of the information retrieval system, which is based on several facts, including the inclination of users, the importance of information and the matching of query. In this article, we firstly introduced the agent-based information retrieval model. Then the multi-weight ranking algorithm, which included in the model, is analyzed. Finally, the performance of the model is discussed and the prototype system is tested through a series of examinations, the result of which addresses the Agent-based information retrieval model with MWRA is better in ranking and other capabilities.
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bound for the generalization error of any...
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Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bound for the generalization error of any voting classifier in terms of the margin distribution over the training data. However, Breiman raised important questions about the margin explanation by developing a boosting algorithm arc-gv that provably generates a larger minimum margin than AdaBoost. He also gave a sharper bound in terms of the minimum margin, and argued that the minimum margin governs the generalization. In experiments however, arc-gv usually performs worse than Ad-aBoost, putting the margin explanation into serious doubts. In this paper, we try to give a complete answer to Breiman's critique by proving a bound in terms of a new margin measure called Equilibrium margin (Emargin). The Emargin bound is uniformly sharper than Breiman's minimum margin bound. This result suggests that the minimum margin is not crucial for the generalization error. We also show that a large Emargin implies good generalization. Experimental results on benchmark datasets demonstrate that AdaBoost usually has a larger Emargin and a smaller test error than arc-gv, which agrees well with our theory.
In agent architecture, active goal is a functionally self-contained entity with independent control flow. The related syntax of active goal and the operational semantics of active goal execution are presented;furtherm...
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In agent architecture, active goal is a functionally self-contained entity with independent control flow. The related syntax of active goal and the operational semantics of active goal execution are presented;furthermore the BDI agent architecture driven by active goals is formally specified. Distinguished from some former BDI agent architecture, goals are not implicitly represented but are explicitly represented in the agent architecture as active entities. Parallel goals are supported in the architecture level with a very natural fashion, which is considered as an important aspect of the rational behavior of agent. What's more, the explicitly definition of goals provide convenience to the reconsideration of commitments for agents situated in dynamic environment.
Biclustering of the gene expressing data is an important task in bioinformatics. By clustering the gene expressing data obtained under different experimental conditions, function and regulatory elements of the gene se...
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Magnetic measurements were performed on apparently deformed igneous rocks of 23 sites from the southeastern part of the Taimyr Peninsula. Rock magnetism and reflected light microscopy analyses reveal that fine-grained...
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Magnetic measurements were performed on apparently deformed igneous rocks of 23 sites from the southeastern part of the Taimyr Peninsula. Rock magnetism and reflected light microscopy analyses reveal that fine-grained titanomagnetites up to pure magnetites mainly carry the majority of magnetic fabrics in the sills, and that the slightly coarser Ti-poor or -medium titanomagnetites carry most mag-netic fabrics in the basaltic flows. Magnetic anisotropies were determined by applying anisotropy of low-field magnetic susceptibility (AMS) on 180 unheated samples and 128 samples that had been pre-viously heated to 600°C during a paleomagnetic study to detect heating effects on the anisotropy of magnetic susceptibility (AMS) properties of volcanic rocks. laboratory heating significantly affects anisotropy variations of these igneous rocks corresponding to the mineralogical changes during the heat treatment.
Large-scale software systems usually consist of a huge number of modules, and have a series of releases along with these modules. This can be seen as software evolution. In recent years, researchers have put forward s...
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Large-scale software systems usually consist of a huge number of modules, and have a series of releases along with these modules. This can be seen as software evolution. In recent years, researchers have put forward several models of software evolution by employing the theory of complex networks. In this paper, we put forward a refined model of software evolution based on the BA model: module-based evolution. We theoretically prove that the power-law degree distribution can be held in our model. We also build a tool to construct and analyze the class diagrams of JDK (Java Development Kits) evolved from version 1.2 to 1.6. The class diagrams can be seen as complex networks under evolution. We apply the module-based evolution model to these complex networks and simulate the evolution of key network features such as average clustering coefficient and average path length. Compared with real networks, our model can precisely describe the evolution of these features, and be used to help developers understand the characteristics of large-scale software evolution.
Data race occurs when multiple threads simultaneously access shared data without appropriate synchronization, and at least one is write. System with a data race is nondeterministic and may generate different outputs e...
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Data race occurs when multiple threads simultaneously access shared data without appropriate synchronization, and at least one is write. System with a data race is nondeterministic and may generate different outputs even with the same input, according to different interleaving of data access. We present a model-based approach for detecting data races in concurrent Java programs. We extend UML Activity diagrams with data operation tags, to model program behavior. Program under test (PUT) is instrumented according to the model. It is then executed with random test cases generated based on path analysis of the model. Execution traces are reverse engineered and used for post-mortem verification. First, data races are identified by searching the time overlaps of entering and exiting critical sections of different threads. Second, implementation could be inconsistent with the design. The problem may tangle with race condition and makes it hard to detect races. We compare the event sequences with the behavior model for consistency checking. Identified inconsistencies help debuggers locate the defects in the PUT. A prototype tool named tocAj implements the proposed approach and was successfully applied to several cases studies.
Data gathering is a common but critical operation in many applications of wireless sensor networks. The innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. As a no...
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Data gathering is a common but critical operation in many applications of wireless sensor networks. The innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. As a novel information acquiring and processing technology, multimedia sensor networks, in contrast to the traditional sensor networks, pay more attention to the multimedia data (e.g., audio, image and video). However, the traditional sensor nodes with low power and small storage are not suitable for in-network processing and storing in data centric applications. We propose CBSM, a new collaboration based storage management scheme in wireless multimedia sensor networks, which better suits the random event sensing and data gathering; furthermore, it applies a novel resource-based method to balancing the energy and storage consuming among nodes, which adjusts packet size in communication dynamically to prolong the network lifetime. Our experiments demonstrate that CBSM can improve the network lifetime drastically even using the existing energy-constraint and storage-constraint sensor nodes.
Since infrared images reflect the temperature-field distributing of vein¿s embranchment of the face, expression recognition from them should focus on changes of thermal distribution on facial muscles and blood ve...
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Since infrared images reflect the temperature-field distributing of vein¿s embranchment of the face, expression recognition from them should focus on changes of thermal distribution on facial muscles and blood vessels, which caused by mood variety. These thermal changes can be regarded as texture features of images. Wavelet transform is a good tool to analyze multi-scale, multi- direction changes of texture. Therefore, this paper presented a facial expression recognition method from thermal images using wavelet transform. Firstly, the status quo of the researches on infrared facial expression recognitions was briefly surveyed and analyzed. Secondly, wavelet transforms were used to extract image features. Thirdly, the ¿Euclidian Distance Maximizing Method¿ we proposed was adopted to select features. Then principal component analysis was employed to reduce feature dimension and NN was used as a classifier. Finally, experiments on medium-wave thermal facial expressions database of Equinox evaluated the effectiveness of our approach.
For the limited bandwidth and other limiting factors in the video coding, the visual quality always cannot satisfy the clients, especially the subjective visual quality. This paper proposes a novel ROI-based rate cont...
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For the limited bandwidth and other limiting factors in the video coding, the visual quality always cannot satisfy the clients, especially the subjective visual quality. This paper proposes a novel ROI-based rate control scheme for H.264/AVS, aiming at improving the subjective visual quality. In our scheme, an efficient method is presented for extracting Region-of-Interest (ROI) adaptively and exactly with introducing some new concepts. Relatively more bits are allocated to Region-of-Interest and the frames with high complexity. The extensive experimental results show that proposed rate control scheme can control bit rates more accurately and achieve better subjective visual quality than the rate control scheme JVT-G012 in the latest JVT H.264/AVC reference model JM11.0.
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