The related theories of Web and Web mining in semantic are concluded and analyzed in this paper. The description on RDF resource is analyzed on the semantic step, and the clustering method for RDFMS data clustering ba...
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ISBN:
(纸本)9780769549583;9781467356039
The related theories of Web and Web mining in semantic are concluded and analyzed in this paper. The description on RDF resource is analyzed on the semantic step, and the clustering method for RDFMS data clustering based on Semantic distance is proposed, with the detailed description for the algorithm and examples. With the discussion on the data mining techniques for semantic Web mining, the design on inductive logic programming is proposed for the data mining techniques that are suitable to the semantic Web. Additionally, how to apply to the description of the algorithm is given through the specific examples to verify the feasibility for the data mining in the semantic Web environment.
The Branch-and-Bound (B& B) method is a wellknown optimization algorithm for solving integer linear programming (ILP) models in the field of operations research. It is part of software often employed by businesses...
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ISBN:
(纸本)9781479907298
The Branch-and-Bound (B& B) method is a wellknown optimization algorithm for solving integer linear programming (ILP) models in the field of operations research. It is part of software often employed by businesses for finding solutions to problems such as airline scheduling problems. It operates according to a divide-and-conquer principle by building a treelike structure with nodes that represent linear programming (LP) problems. A LP solver commonly used to process the nodes is the simplex method. Nowadays its sequential implementation can be found in almost all commercial ILP solvers. In this paper, we present a hybrid CPU-GPU implementation of the B&B algorithm. The B&B tree is managed by the CPU, while the revised simplex method is mainly a GPU implementation, relying on the CUDA technology of NVIDIA. The CPU manages concurrently multiple instances of the LP solver. The principal difference with a sequential implementation of the B&B algorithm pertains to the LP solver, provided that the B&B tree is managed with the same strategy. We thus compared our GPU-based implementation of the revised simplex to a wellknown open-source sequential solver, named CLP, of the COINOR project. For given problem densities, we measured a size threshhold beyond which our GPU implementation outperformed its sequential counterpart.
For some computer vision tasks, such as location recognition on mobile devices or Structure from Motion (SfM) computation from Internet photo collections, one wants to reduce a large set of images to a compact, repres...
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ISBN:
(纸本)9781479930227
For some computer vision tasks, such as location recognition on mobile devices or Structure from Motion (SfM) computation from Internet photo collections, one wants to reduce a large set of images to a compact, representative subset, sometimes called "keyframes" or "skeletal set". We examine the problem of selecting a minimum set of such keyframes from the point of view of discrete optimization, as the search for a minimum connected dominating set (CDS) of the graph of pairwise connections between the database images. Even the simple minimum dominating set (DS) problem is known to be NP-hard, and the constraint that the dominating set should be connected makes it even harder. We show how the minimum DS can nevertheless be solved to global optimality efficiently in practice, by formulating it as an integer linear program (ILP). Furthermore, we show how to upgrade the solution to a connected dominating set with a second ILP if necessary, although the complete method is no longer globally optimal. We also compare the proposed method to a previous greedy heuristic. Experiments with several image sets show that the greedy solution already performs remarkably well, and that the optimal solution achieves roughly 5% smaller keyframe sets which perform equally well in location recognition and SfM tasks.
Connection requests for data-intensive applications often require specific start time and end time/duration when they are submitted. With the additional time domain information, cost efficient connections can be estab...
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ISBN:
(纸本)9781467349840;9781467349857
Connection requests for data-intensive applications often require specific start time and end time/duration when they are submitted. With the additional time domain information, cost efficient connections can be established. In this paper, we propose two capital expenditure (CapEx) optimized approaches: Multi-Layer (ML) approach and Transponder/Regenerator Reuse (TRR) approach. Integer Linear programming (ILP) is used to formulate the routing, wavelength assignment and regenerator/multiplexer placement problem in a complex multi-layer optical network and provide lower bounds for the optimized CapEx value. Due to the time and space complexity of ILP, we also propose a greedy algorithm and a tabu-search algorithm to solve the same problem in a less time and resource consuming way. Finally, we compare the results in terms of computing time and optimized CapEx value across the ILP, greedy heuristic and tabu search heuristic methods with the ML approach for the Internet2 topology and a 6-node ring topology. The performance of all three methods with TRR approach is also tested with the same input traffic. The results show 30% to 40% less CapEx when comparing ML with TRR. Further, our tabu search heuristic can achieve near optimal results compared to ILP.
Concept discovery systems are concerned with learning definitions of a specific relation in terms of other relations provided as background knowledge. Although such systems have a history of more than 20 years and suc...
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ISBN:
(纸本)9783642408465
Concept discovery systems are concerned with learning definitions of a specific relation in terms of other relations provided as background knowledge. Although such systems have a history of more than 20 years and successful applications in various domains, they are still vulnerable to scalability and efficiency issues - mainly due to large search spaces they build. In this study we propose a heuristic to select a target instance that will lead to smaller search space without sacrificing the accuracy. The proposed heuristic is based on counting the occurrences of constants in the target relation. To evaluate the heuristic, it is implemented as an extension to the concept discovery system called (CD)-D-2. The experimental results show that the modified version of (CD)-D-2 builds smaller search space and performs better in terms of running time without any decrease in coverage in comparison to the one without extension.
RWA is a fundamental problem in the design and control of optical networks. We propose link selection algorithms that reduce the size of the link-based ILP formulation for RWA by pruning redundant link decision variab...
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ISBN:
(纸本)9781479904914
RWA is a fundamental problem in the design and control of optical networks. We propose link selection algorithms that reduce the size of the link-based ILP formulation for RWA by pruning redundant link decision variables. The resulting formulation scales well to mesh topologies representative of backbone and regional networks. In our experiments, the new formulation decreases the running time by more than two orders of magnitude without any impact on optimality. The link selection techniques are general in that they may be applied to any optimization problem for which the ILP formulation consists of multicommodity flow equations as its core constraints.
This paper introduces a new implementation of Shared Segment Protection (SSP) in mesh communication networks, in which a novel Integer Linear Program (ILP) is proposed under a reduced amount of routing information. In...
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ISBN:
(纸本)9781479915439;9781479915460
This paper introduces a new implementation of Shared Segment Protection (SSP) in mesh communication networks, in which a novel Integer Linear Program (ILP) is proposed under a reduced amount of routing information. In particular, the scheme of Distributed Partial Information Management with Sufficient and Aggregated Information (DPIM-SAM) [1] will be adopted for trading the optimality with the reduction on the computation time. We will verify the ILP formulation by comparing its result with the cases of SSP and Path Shared Protection under the complete routing information scenario (SCI) in terms of performance and computation time.
This paper provides a logical framework for comparing inductive capabilities among agents having different background theories. A background theory is called inductively equivalent to another background theory if the ...
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This paper provides a logical framework for comparing inductive capabilities among agents having different background theories. A background theory is called inductively equivalent to another background theory if the two theories induce the same hypotheses for any observation. Conditions of inductive equivalence change depending on the logic of representation languages and the logic of induction or inductive logic programming (ILP). In this paper, we consider clausal logic and nonmonotonic logic programs as representation languages for background theories. Then we investigate conditions of inductive equivalence in four different frameworks of induction, cautious induction , brave induction , learning from satisfiability , and descriptive induction . We observe that several induction algorithms in Horn ILP systems require weaker conditions of equivalence under restricted problem settings. We address that inductive equivalence can be used for verification and evaluation of induction algorithms, and argue problems for optimizing background theories in ILP.
We propose an ILP model and an efficient rescaled failure-probability-aware algorithm (RFPA) to minimize spectral resource consumption. Simulation results show that, compared to a traditional algorithm, both ILP model...
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ISBN:
(纸本)9781557529626;9781479904570
We propose an ILP model and an efficient rescaled failure-probability-aware algorithm (RFPA) to minimize spectral resource consumption. Simulation results show that, compared to a traditional algorithm, both ILP model and RFPA achieve higher spectrum efficiency.
Recent advances in information extraction have led to huge knowledge bases (KBs), which capture knowledge in a machine-readable format. inductive logic programming (ILP) can be used to mine logical rules from the KB. ...
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ISBN:
(纸本)9781450320351
Recent advances in information extraction have led to huge knowledge bases (KBs), which capture knowledge in a machine-readable format. inductive logic programming (ILP) can be used to mine logical rules from the KB. These rules can help deduce and add missing knowledge to the KB. While ILP is a mature field, mining logical rules from KBs is different in two aspects: First, current rule mining systems are easily overwhelmed by the amount of data (state-of-the art systems cannot even run on today's KBs). Second, ILP usually requires counterexamples. KBs, however, implement the open world assumption (OWA), meaning that absent data cannot be used as counterexamples. In this paper, we develop a rule mining model that is explicitly tailored to support the OWA scenario. It is inspired by association rule mining and introduces a novel measure for confidence. Our extensive experiments show that our approach outperforms state-of-the-art approaches in terms of precision and coverage. Furthermore, our system, AMIE, mines rules orders of magnitude faster than state-of-the-art approaches.
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