Based heuristic

Xem 1-20 trên 68 kết quả Based heuristic
  • A routing algorithm constructs routing tables to forward communication packets based on network status information. Rapid inflation of the Internet increases demand for scalable and adaptive network routing algorithms. Conventional protocols such as the Routing Information Protocol (RIP) (Hedrick, 1988) and the Open Shortest-Path First protocol (OSPF) (Comer, 1995) are not adaptive algorithms; they because they only rely on hop count metrics to calculate shortest paths. In large networks, it is difficult to realize an adaptive algorithm based on conventional approaches. ...

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  • Channel Assignment Problems (CAPs) occur in the design of cellular mobile telecommunication systems (Jordan, 1996; Katzela and Naghshineh, 1996; MacDonald, 1979); such systems typically divide the geographical region to be serviced into a set of cells, each containing a base station. The available radio frequency spectrum is divided into a set of disjoint channels; these must be assigned to the base stations to meet the expected demand of each cell and to avoid electromagnetic interference during calls....

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  • In the last two decades, wireless communication systems such as cordless phones, paging systems, wireless data networks, satellite-based and cellular mobile systems have been steadily increasing in both popular importance and technological sophistication. The firstgeneration wireless systems were developed in the late 1970s and 1980s and were based on analog technology (such as the Advance Mobile Phone Service (AMPS) by AT&T and Nordic Mobile Telephone (NMT) by Ericsson).

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  • This paper considers the problem of dynamic survivable routing in WDM networks with single link failure model. This work mainly concerns in how to dynamically determine a protection cycle (i.e., two link-disjoint paths between a node pair) to establish a dependable lightpath with backup paths sharing. The problem is identified as NP-complete, thus a heuristic for finding near optimal solution with reasonable computation time is usually preferred.

    pdf9p tuanlocmuido 19-12-2012 28 2   Download

  • Unsupervised word alignment is most often modeled as a Markov process that generates a sentence f conditioned on its translation e. A similar model generating e from f will make different alignment predictions. Statistical machine translation systems combine the predictions of two directional models, typically using heuristic combination procedures like grow-diag-final. This paper presents a graphical model that embeds two directional aligners into a single model.

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  • Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web’s natural language text. Knowledge-based weak supervision, using structured data to heuristically label a training corpus, works towards this goal by enabling the automated learning of a potentially unbounded number of relation extractors.

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  • Transition-based dependency parsers generally use heuristic decoding algorithms but can accommodate arbitrarily rich feature representations. In this paper, we show that we can improve the accuracy of such parsers by considering even richer feature sets than those employed in previous systems. In the standard Penn Treebank setup, our novel features improve attachment score form 91.4% to 92.9%, giving the best results so far for transitionbased parsing and rivaling the best results overall. For the Chinese Treebank, they give a signficant improvement of the state of the art. ...

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  • Syntactic knowledge is important for pronoun resolution. Traditionally, the syntactic information for pronoun resolution is represented in terms of features that have to be selected and defined heuristically. In the paper, we propose a kernel-based method that can automatically mine the syntactic information from the parse trees for pronoun resolution. Specifically, we utilize the parse trees directly as a structured feature and apply kernel functions to this feature, as well as other normal features, to learn the resolution classifier.

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  • This paper presents a new bottom-up chart parsing algorithm for Prolog along with a compilation procedure that reduces the amount of copying at run-time to a constant number (2) per edge. It has applications to unification-based grammars with very large partially ordered categories, in which copying is expensive, and can facilitate the use of more sophisticated indexing strategies for retrieving such categories that may otherwise be overwhelmed by the cost of such copying.

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  • Syntactic knowledge is important for discourse relation recognition. Yet only heuristically selected flat paths and 2-level production rules have been used to incorporate such information so far. In this paper we propose using tree kernel based approach to automatically mine the syntactic information from the parse trees for discourse analysis, applying kernel function to the tree structures directly.

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  • This paper presents an approach for Multilingual Document Clustering in comparable corpora. The algorithm is of heuristic nature and it uses as unique evidence for clustering the identification of cognate named entities between both sides of the comparable corpora. One of the main advantages of this approach is that it does not depend on bilingual or multilingual resources. However, it depends on the possibility of identifying cognate named entities between the languages used in the corpus.

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  • We present an improved method for automated word alignment of parallel texts which takes advantage of knowledge of syntactic divergences, while avoiding the need for syntactic analysis of the less resource rich language, and retaining the robustness of syntactically agnostic approaches such as the IBM word alignment models. We achieve this by using simple, easily-elicited knowledge to produce syntaxbased heuristics which transform the target language (e.g.

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  • Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinations are crucial to improving performance, they are heuristically selected. Kernel methods change this situation. The merit of the kernel methods is that effective feature combination is implicitly expanded without loss of generality and increasing the computational costs.

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  • This paper presents a corpus-based approach for deriving heuristics to locate the antecedents of relative pronouns. The technique dupficates the performance of hand-coded rules and requires human intervention only during the training phase. Because the training instances are built on parser output rather than word cooccurrences, the technique requires a small number of training examples and can be used on small to medium-sized corpora.

    pdf8p bunmoc_1 20-04-2013 21 1   Download

  • We present a program for segmenting texts according to the separate events they describe. A modular architecture is described that allows us to examine the contributions made by particular aspects of natural language to event structuring. This is applied in the context of terrorist news articles, and a technique is suggested for evaluating the resulting segmentations. We also examine the usefulness of various heuristics in forming these segmentations.

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  • In this paper, we present a feature-based method to align documents with similar content across two sets of bilingual comparable corpora from daily news texts. We evaluate the contribution of each individual feature and investigate the incorporation of these diverse statistical and heuristic features for the task of bilingual document alignment. Experimental results on the English-Chinese and EnglishMalay comparable news corpora show that our proposed Discrete Fourier Transformbased term frequency distribution feature is very effective. ...

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  • The goal of the SaaS provider is the most profitable; the user’s goal is to meet requirements as quickly as possible but still within budget and deadline. In this paper, a heuristic ACO (Ant Colony Optimization) is used to propose an algorithm to admission control, then building a scheduling algorithm based on the overlapping time between requests.

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  • Risk management is recognized as an essential contributor to business and project success, since it focuses on addressing uncertainties in a proactive manner in order to minimize threats, maximize opportunities and optimize achievement of objectives. There is wide convergence and international consensus on the necessary elements for a risk management process, and this is supported by a growing range of capable tools and techniques, an accepted body of knowledge, an academic and research base, and wide experience of practical implementation across many industries....

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  • In this paper, we present an audio-based event detection approach shown to be effective when applied to the Sports broadcast data. The main benefit of this approach is the ability to recognise patterns that indicate high levels of crowd response which can be correlated to key events.

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  • We do some initial processing of the raw-format mes- sages before the next step. The rst is to extract a reli- able sender IP address heuristically for each message. Al- though the message format dictates a chain of relaying IP addresses in each message, a malicious relay can easily al- ter that. Therefore we cannot simply take the rst IP in the chain. Instead, our method is as follows (similar to the one in [5]). First we trust the sender IP reported by Hot- mail in the Received headers, and if the previous relay IP address (before any server from Hotmail) is on our trust list (e.g.

    pdf9p nhacsihuytuan 06-04-2013 19 4   Download


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