edge weights
Optimization and visualization of the edge weights in optimal assignment methods for virtual screening
... Changing the edge weights, in particular driving weights close to zero, can dramati- cally change the OA. Changing the OA of several library compounds results in a different VS result. Thus, the ...
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Aggregating Edge Weights in Social Networks on the Web Extracted from Multiple Sources with Different Importance Degrees
... extracted from various sources on the Web. Due to the large volume of information available, data received will rarely be the same. To evaluate these data, there needs to be a way to rank these sources. Omitting ...
5
GoWvis: A Web Application for Graph of Words based Text Visualization and Summarization
... Related work. Similarly, (Bougouin et al., 2013) have used clustering and graph mining for keyphrase extraction, but the other way around. They first group candidate keyphrases into topics via hierarchical clustering ...
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Spectra and structural polynomials of graphs of relevance to the theory of molecular conduction
... The algebraic development of structural polynomials reported here has been carried out in order to have exact results on which to base an elaboration of the theory of molecular conduction. The new formulae will allow us ...
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Weight Identification of a Weighted Bipartite Graph Complex Dynamical Network with Coupling Delay
... the weights of the ...the edge weights between nodes of the network by monitoring the dynamical evolution of the synchronous networks with drive-response ...
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Simultaneous Similarity Learning and Feature Weight Learning for Document Clustering
... We also compare our algorithm against the follow- ing algorithms SC-MV: We compare our algorithm against the spectral classification algorithm for data with multiple views (Zhou and Burges, 2007). The algorithm tries to ...
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Multistructure Diffeomorphic Brain Registration
... Here Gaussian filter is used to process the input images. Then Segment the white matter with a Meanshift segmentation will be applied. The edge weights are computed from the relative positions of the ...
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PREVENTION AGAINST HACKING USING DIJKSTRA ALGORITHM
... This algorithm is greedy because we assume we have a shortest distance to a vertex before we ever examine all the edges that even lead into that vertex. In general, this works because we assume no negative edge ...
8
VISIR-1.b: ocean surface gravity waves and currents for energy-efficient navigation
... Figure 3b shows that peak RAM increases to about 3 × 10 8 DOF, where it saturates. Here, the computer’s physical memory limit is approached, which leads to swapping and to a degradation of performance, as already ...
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Unrestricted Coreference Resolution via Global Hypergraph Partitioning
... assigned weights which are calculated on the training data as the percentage of the initial edges being in fact ...assigning edge weights, only a reasonable size of training data is ...
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Vol 9, No 5 (2018)
... the edge weights are triangular fuzzy numbers and trapezoidal fuzzy numbers and prove that the fuzzy α -minimum spanning tree problem can be transformed to a classical problem on a crisp graph in these two ...
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Fast algorithms for shortest paths
... The second algorithm presented, and the main result of this thesis, has an expected running time of On 2logn on graphs with edge weights drawn from an endpoint independent probability di[r] ...
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Improved Algorithms for Document Classification &Query-based Multi-Document Summarization
... 1) Hypergraph based semi-supervised sentence ranking for query oriented summarization [8]: In this algorithm, the document is represented as a hypergraph, in which the sentences (along with the query) are represented as ...
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Unsupervised Abstractive Meeting Summarization with Multi Sentence Compression and Budgeted Submodular Maximization
... As shown in Figure 5, a word graph is constructed with special edge weights, the K-shortest weighted paths are then found and re-ranked with a scoring function, and the best path is used[r] ...
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Learning Graph Walk Based Similarity Measures for Parsed Text
... Experimental setup. We evaluated cross-validation performance over the training queries in terms of mean average precision for varying walk lengths K. We found that beyond K = 6 improvements were small (and in fact ...
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Estimating psychological networks and their accuracy: A tutorial paper
... estimated edge-weights, (B) assess the stability of centrality indices after subsetting the data, and (C) test if edge-weights and centralities differ from one- ...bootstrapping ...
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Use of DAG in Distributed Parallel Computing
... vertex/node weights represent task processing time and the edge weights represent data dependencies as well as the communication time between ...an edge is called the parent node while the ...
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The On-Line Shortest Path Problem Under Partial Monitoring
... whose edge weights can change in an arbitrary (adversarial) way, a decision maker has to choose in each round of a game a path between two distinguished vertices such that the loss of the chosen path ...
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Subjectivity Recognition on Word Senses via Semi supervised Mincuts
... construct edge weights to classification vertices us- ing the SVM discussed above and use WordNet re- lations for links between example vertices, weighted by either constants (NoSL) or via the method illus- ...
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Cross-national agreement on disability weights: the European Disability Weights Project
... disability weights in Western European countries with VAS and TTO methods, but a lower level of agreement with the PTO ...disability weights was insufficient when a societal perspective was taken into ...
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