In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an...
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In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained some hints about further approach to the hypotheses. on a real-world dataset, we try to give knowledge-driven validations of such
Here, we propose a technique to acquire knowledge for baseball digest video production using an inductive inference approach. We integrated the concept of inductive logic programming (ILP) and baseball game metadata t...
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ISBN:
(纸本)9781424440894
Here, we propose a technique to acquire knowledge for baseball digest video production using an inductive inference approach. We integrated the concept of inductive logic programming (ILP) and baseball game metadata to enable learning of the highlight scene definition from digest video produced by a TV director ILP is a learning method formed at the intersection of machine learning and logicprogramming, and ILP processor can acquire the highlight scene definition by inductive learning from scenes that are selected as highlights in sports news. This technique makes it possible to generate a semantic digest automatically, which includes not only score scenes hut also attractive scenes reflecting the director's intention.
Software libraries organize useful functionalities in order to promote modularity and code reuse. A typical library is used by client programs through an application programming interface (API) that hides its internal...
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ISBN:
(纸本)9781605580791
Software libraries organize useful functionalities in order to promote modularity and code reuse. A typical library is used by client programs through an application programming interface (API) that hides its internals from the client. Typically, the rules governing the correct usage of the API are documented informally. In many cases, libraries may have complex API usage rules and unclear documentation. As a result, the behaviour of the library under some corner cases may not be well understood by the programmer. Formal specifications provide a precise understanding of the API behaviour. We propose a methodology for learning interface specifications using inductive logic programming (ILP). Our technique runs several unit. tests on the library in order to generate relations describing the operation of the library. The data collected from these tests are used by an inductive learner to obtain rich Datalog/Prolog specifications. Such specifications capture essential properties of interest to the user. They may be used for applications such as reverse engineering the library internals or constructing checks on the application code to enforce proper API usage along with other properties of interest.
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.
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.
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.
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