acyclic graph
Hierarchical Directed Acyclic Graph Kernel: Methods for Structured Natural Language Data
... This paper proposes the “Hierarchical Di- rected Acyclic Graph (HDAG) Kernel” for structured natural language data. The HDAG Kernel directly accepts several lev- els of both chunks and their relations, and ...
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Constructing Directed Acyclic Graph of Independent Tasks using Deadlines for Scheduling
... The grids are heterogeneous and dynamic environments consisting of network, storage and computing resources. The resources are sorted based on the processing power. Resources that are able to complete the given set of ...
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Sentiment Sentence Extraction Using a Hierarchical Directed Acyclic Graph Structure and a Bootstrap Approach
... In this paper, we propose a method of sentiment sentence extraction. It uses several sample sentences for the extraction process. In the process, we compute a similarity between the sample sentences and target sentences. ...
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Mining Knowledge Of The Directed Acyclic Graph (DAG) And Dataset Using The Hill Climbing Algorithm
... Hill Climbing is basically an optimization algorithm that works how to test each node or data point. When the data point meets the target function that evaluates the data point and its value is better than the previous ...
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An Efficient Technique for Multipath Routing Based on Directed Acyclic Graph (DAG) Amit Sawanni, Diamond Jonawal
... Abstract--Today’s era is facing ever increasing demand of a network. This huge demand is leading to network troubleshooting and recovery from network failure. To accommodate this diverse need of network we utilize the ...
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A Transition Based Directed Acyclic Graph Parser for UCCA
... Several transition-based AMR parsers have been proposed: CAMR assumes syntactically parsed input, processing dependency trees into AMR (Wang et al., 2015a,b, 2016; Goodman et al., 2016). In contrast, the parsers of ...
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Coarse grained and Fine grained Analytics in a Single Framework
... Second generation of data analytics frameworks introduced interactive an- alytics into the picture. Apache Tez is a good example of this. It is an extensible framework for building high performance batch and interactive ...
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Title: Predicting Dengue Using Bayes Net Classifier
... It is a Probabilistic model or statistical model, which consists of set of variables and their Conditional dependencies through Directed Acyclic Graph. It can also used for representating the relationship ...
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Use of DAG in Distributed Parallel Computing
... Directed Acyclic Graph(DAG)[11], in which the vertex/node weights represent task processing time and the edge weights represent data dependencies as well as the communication time between ...Directed ...
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Bayesian Network Learning via Topological Order
... the graph such that the graph contains arc (u, v) if and only if u appears before v in the order (Cormen et ...an acyclic graph. Then, by sorting the nodes of acyclic graph G(Z) ...
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Analysis Study of Routing Protocols in MANET
... Directed Acyclic Graph (DAG) of the route from the source node to the destination In this protocol, direction of the link between two nodes determined by height ...
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Enhanced DAGitizer for Grid Computing through the Discovery of Least Cost Path
... Acyclic Graph. Grid Workflow scheduling is replicated through Directed Acyclic Graph, and the paper focuses on the generation of effective DAG, which is made in a much automated way through ...
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HPSG Parsing with Shallow Dependency Constraints
... While a number of fairly straightforward models can be applied successfully to dependency parsing, de- signing and training HPSG parsing models has been regarded as a significantly more complex task. Al- though it seems ...
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Comparing Constraints for Taxonomic Organization
... taxonomic graph, whether they specify that the final graph structure be a directed acyclic graph (DAG) or tree/forest, and whether they identify ‘clusters’ of synonymous ...
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Implementation Methodology of Real-Valued Augmented Simulated Annealing Algorithm for Dependent Task Scheduling
... Directed Acyclic Graph (DAG), the scheduling problem deals with mapping each task of the application onto the available heterogeneous systems in order to minimize makespan ...
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On maximum spanning DAG algorithms for semantic DAG parsing
... A directed acyclic graph (DAG) is a directed graph with no cycles. There is a special kind of DAG, which has a special node called a root with no incoming edges and in which there is a unique path ...
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Strong Complementary Acyclic Domination of a Graph
... sub graph of a graph G is called a component of ...the graph with vertex set V in which two vertices are adjacent if and only if they are not adjacent in ...A graph G is said to be ...
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Counting and Sampling Markov Equivalent Directed Acyclic Graphs
... In causal discovery a key task is to learn a directed acyclic graph (DAG) on the variables of interest. What makes learn- ing particularly challenging is that different DAGs can repre- sent the same ...
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A study of Mobile Ad-hoc Network-Challenges, Characteristics, Applications and Routing
... It is a reactive routing protocol where link between nodes is established creating using Directed Acyclic Graph (DAG) of the route from the source node to the destination. It uses link reversal model in ...
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Correlation between the Topic and Documents Based on the Pachinko Allocation Model
... The pachinko allocation model (PAM), which uses a directed acyclic graph (DAG) structure to represent and learn arbitrary- arity, nested, and possibly sparse topic correlations. In PAM, the concept of ...
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