This paper presents the results of our participation in the relevance feedback track using our novel retrieval models. These models simulate human relevance decision-making. For each document location of a query term,...
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This paper presents the results of our participation in the relevance feedback track using our novel retrieval models. These models simulate human relevance decision-making. For each document location of a query term, information from its document-context at that location determines the relevance decision outcomes there. The relevance values for all documents locations of all query terms in the same document are combined to form the final relevance value for that document. Two probabilistic models are developed, and one of them is directly related to the TF-IDF term weights. Our initial retrieval is a passage-based retrieval. Passage scores of the same document are combined by the Dombi fuzzy disjunction operator. Later, we found that the Markov random field (MRF) model produces better results than our initial retrieval system (without relevance information). If we apply our novel retrieval models using the initial retrieval list of the MRF model, the retrieval effectiveness of our models will be improved. These informal run results using the MRF model used in conjunction with our novel models are also presented.
Stochastic approximation problem is to find some root or extremum of a nonlinear function for which only noisy measurements of the function are available. The classical algorithm for stochastic approximation problem i...
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Stochastic approximation problem is to find some root or extremum of a nonlinear function for which only noisy measurements of the function are available. The classical algorithm for stochastic approximation problem is the Robbins-Monro (RM) algorithm, which uses the noisy evaluation of the negative gradient direction as the iterative direction. In order to accelerate the RM algorithm, this paper gives a flame algorithm using adaptive iterative directions. At each iteration, the new algorithm goes towards either the noisy evaluation of the negative gradient direction or some other directions under some switch criterions. Two feasible choices of the criterions are proposed and two corresponding frame algorithms are formed. Different choices of the directions under the same given switch criterion in the frame can also form different algorithms. We also proposed the simultanous perturbation difference forms for the two frame algorithms. The almost surely convergence of the new algorithms are all established. The numerical experiments show that the new algorithms are promising.
Giving examples to students or letting students give examples is important in ordinary instruction. However, it is difficult for teacher to provide work-out examples to students since the proper examples are depending...
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Quality assurance is recognized as a critical aspect in software construction. SAM is a formal software architecture description model that combines Petri Nets and Temporal Logic. PROMELA is the language used in the S...
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ISBN:
(纸本)9781627486620
Quality assurance is recognized as a critical aspect in software construction. SAM is a formal software architecture description model that combines Petri Nets and Temporal Logic. PROMELA is the language used in the Spin model checker. This paper presents an approach to translate a restricted SAM model to a PROMELA program, enabling the model checking of the SAM model. We define the translation and show its correctness in terms of completeness and consistency. Completeness establishes that a SAM model maps all of its elements to PROMELA ones;whereas, consistency defines that an execution of a SAM model has a corresponding execution in a PROMELA program. The translation is also implemented as part of our software tool supporting SAM. Some aspects of the tool are discussed.
In wireless sensor networks (WSN), sensor location plays a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-fre...
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With the fast development of video semantic analysis, there has been increasing attention to the typical issue of the semantic analysis of soccer program. Based on the color feature analysis, this paper focuses on the...
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In this paper, a robust image watermarking approach is presented based on image local invariant features. The affine invariant point detector is used to extract feature regions of the given host image. Image normaliza...
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The development of context-aware systems such as groupware or CSCW and ubiquitous systems require a significant understanding of specific tasks that the users will perform seamlessly in their everyday work. In order t...
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The development of context-aware systems such as groupware or CSCW and ubiquitous systems require a significant understanding of specific tasks that the users will perform seamlessly in their everyday work. In order to do this, we need to understand the users' tasks and their knowledge to perform these tasks, and build a computational model reflecting upon users' tasks and their knowledge. Most importantly, such systems need to be socially appropriate so that they can support human- human communication in an implicit and unobtrusive way, by constantly monitoring humans, their activities and their intentions. The traditional methods of requirements capture are not suitable to design and develop such systems. In this paper, we discuss different models and theories that can help to gather requirements. Most importantly, a simulation can play an important role in the requirements engineering processes of such systems.
The precision of the answer is now essential for a question answering system, because of the large amount of free texts on the Internet. Attempting to achieve a high precision, we propose a question answering system s...
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ISBN:
(纸本)9781424427802
The precision of the answer is now essential for a question answering system, because of the large amount of free texts on the Internet. Attempting to achieve a high precision, we propose a question answering system supported by case grammar theory and based on VerbNet frames. It extracts the syntactic, thematic and semantic information from the question to filter out unmatched sentences in semantic level and to extract answer chunk (a phrase or a word that can answer the question) from the answer sentence. VerbNet is applied in our system to detect the verb frames in question and candidate sentences, so that the syntactic and thematic information as well as semantic information can be therefore obtained. Our question answering system works well especially for answering factoid questions. The experiments show that our approach is able to filter out semantically unmatched sentences effectively and therefore rank the correct answer (s) higher in the result list.
Large-scale computing environments, such as TeraGrid, Distributed ASCI Supercomputer (DAS), and Gridpsila5000, have been using resource co-allocation to execute applications on multiple sites. Their schedulers work wi...
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Large-scale computing environments, such as TeraGrid, Distributed ASCI Supercomputer (DAS), and Gridpsila5000, have been using resource co-allocation to execute applications on multiple sites. Their schedulers work with requests that contain imprecise estimations provided by users. This lack of accuracy generates fragments inside the scheduling queues that can be filled by rescheduling both local and multi-site requests. Current resource co-allocation solutions rely on advance reservations to ensure that users can access all the resources at the same time. These coallocation requests cannot be rescheduled if they are based on rigid advance reservations. In this work, we investigate the impact of rescheduling co-allocation requests based on flexible advance reservations and processor remapping. The metascheduler can modify the start time of each job component and remap the number of processors they use in each site. The experimental results show that local jobs may not fill all the fragments in the scheduling queues and hence rescheduling co-allocation requests reduces response time of both local and multi-site jobs. Moreover, we have observed in some scenarios that processor remapping increases the chances of placing the tasks of multi-site jobs into a single cluster, thus eliminating the inter-cluster network overhead.
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