The Experts below are selected from a list of 296211 Experts worldwide ranked by ideXlab platform
Kenny Q. Zhu - One of the best experts on this subject based on the ideXlab platform.
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Semantic Bootstrapping: A Theoretical Perspective
IEEE Transactions on Knowledge and Data Engineering, 2017Co-Authors: Haixun Wang, Kenny Q. ZhuAbstract:Knowledge acquisition is an iterative process. Most previous work has focused on Bootstrapping techniques based on syntactic patterns, that is, each iteration finds more syntactic patterns for subsequent extraction. However, syntactic Bootstrapping is incapable of resolving the inherent ambiguities in the syntactic patterns. The precision of the extracted results is thus often poor. On the other hand, semantic Bootstrapping bootstraps directly on knowledge rather than on syntactic patterns, that is, it uses existing knowledge to understand the text and acquire more knowledge. It has been shown that semantic Bootstrapping can achieve superb precision while retaining good recall. Nonetheless, the working mechanism of semantic Bootstrapping remains elusive. In this paper, we present a detailed analysis of semantic Bootstrapping from a theoretical perspective. We show that the efficiency and effectiveness of semantic Bootstrapping can be theoretically guaranteed. Our experimental evaluation results substantiate the theoretical analysis.
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ICDE - Semantic Bootstrapping: A Theoretical Perspective
2017 IEEE 33rd International Conference on Data Engineering (ICDE), 2017Co-Authors: Haixun Wang, Kenny Q. ZhuAbstract:Knowledge acquisition is an iterative process. Most prior work used syntactic Bootstrapping approaches, while semantic Bootstrapping was proposed recently. Unlike syntactic Bootstrapping, semantic Bootstrapping bootstraps directly on knowledge rather than on syntactic patterns, that is, it uses existing knowledge to understand the text and acquire more knowledge. It has been shown that semantic Bootstrapping can achieve superb precision while retaining good recall on extracting isA relation. Nonetheless, the working mechanism of semantc Bootstrapping remains elusive. In this extended abstract, we present a theoretical analysis as well as an experimental study to provide deeper insights into semantic Bootstrapping.
Haixun Wang - One of the best experts on this subject based on the ideXlab platform.
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Semantic Bootstrapping: A Theoretical Perspective
IEEE Transactions on Knowledge and Data Engineering, 2017Co-Authors: Haixun Wang, Kenny Q. ZhuAbstract:Knowledge acquisition is an iterative process. Most previous work has focused on Bootstrapping techniques based on syntactic patterns, that is, each iteration finds more syntactic patterns for subsequent extraction. However, syntactic Bootstrapping is incapable of resolving the inherent ambiguities in the syntactic patterns. The precision of the extracted results is thus often poor. On the other hand, semantic Bootstrapping bootstraps directly on knowledge rather than on syntactic patterns, that is, it uses existing knowledge to understand the text and acquire more knowledge. It has been shown that semantic Bootstrapping can achieve superb precision while retaining good recall. Nonetheless, the working mechanism of semantic Bootstrapping remains elusive. In this paper, we present a detailed analysis of semantic Bootstrapping from a theoretical perspective. We show that the efficiency and effectiveness of semantic Bootstrapping can be theoretically guaranteed. Our experimental evaluation results substantiate the theoretical analysis.
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ICDE - Semantic Bootstrapping: A Theoretical Perspective
2017 IEEE 33rd International Conference on Data Engineering (ICDE), 2017Co-Authors: Haixun Wang, Kenny Q. ZhuAbstract:Knowledge acquisition is an iterative process. Most prior work used syntactic Bootstrapping approaches, while semantic Bootstrapping was proposed recently. Unlike syntactic Bootstrapping, semantic Bootstrapping bootstraps directly on knowledge rather than on syntactic patterns, that is, it uses existing knowledge to understand the text and acquire more knowledge. It has been shown that semantic Bootstrapping can achieve superb precision while retaining good recall on extracting isA relation. Nonetheless, the working mechanism of semantc Bootstrapping remains elusive. In this extended abstract, we present a theoretical analysis as well as an experimental study to provide deeper insights into semantic Bootstrapping.
Vladimir Mitev - One of the best experts on this subject based on the ideXlab platform.
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Bootstrapping pentagon functions
Journal of High Energy Physics, 2018Co-Authors: Dmitry Chicherin, Johannes M. Henn, Vladimir MitevAbstract:In Phys. Rev. Lett. 116 (2016) 062001, the space of planar pentagon functions that describes all two-loop on-shell five-particle scattering amplitudes was introduced. In the present paper we present a natural extension of this space to non-planar pentagon functions. This provides the basis for our pentagon bootstrap program. We classify the relevant functions up to weight four, which is relevant for two-loop scattering amplitudes. We constrain the first entry of the symbol of the functions using information on branch cuts. Drawing on an analogy from the planar case, we introduce a conjectural second-entry condition on the symbol. We then show that the information on the function space, when complemented with some additional insights, can be used to efficiently bootstrap individual Feynman integrals. The extra information is read off of Mellin-Barnes representations of the integrals, either by evaluating simple asymptotic limits, or by taking discontinuities in the kinematic variables. We use this method to evaluate the symbols of two non-trivial non-planar five-particle integrals, up to and including the finite part.
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Bootstrapping pentagon functions
arXiv: High Energy Physics - Theory, 2017Co-Authors: Dmitry Chicherin, Johannes M. Henn, Vladimir MitevAbstract:In PRL 116 (2016) no.6, 062001, the space of planar pentagon functions that describes all two-loop on-shell five-particle scattering amplitudes was introduced. In the present paper we present a natural extension of this space to non-planar pentagon functions. This provides the basis for our pentagon bootstrap program. We classify the relevant functions up to weight four, which is relevant for two-loop scattering amplitudes. We constrain the first entry of the symbol of the functions using information on branch cuts. Drawing on an analogy from the planar case, we introduce a conjectural second-entry condition on the symbol. We then show that the information on the function space, when complemented with some additional insights, can be used to efficiently bootstrap individual Feynman integrals. The extra information is read off of Mellin-Barnes representations of the integrals, either by evaluating simple asymptotic limits, or by taking discontinuities in the kinematic variables. We use this method to evaluate the symbols of two non-trivial non-planar five-particle integrals, up to and including the finite part.
Yuji Matsumoto - One of the best experts on this subject based on the ideXlab platform.
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Semantic Drift in Espresso-style Bootstrapping: Graph-theoretic Analysis and Evaluation in Word Sense Disambiguation
Transactions of the Japanese Society for Artificial Intelligence, 2010Co-Authors: Mamoru Komachi, Taku Kudo, Masashi Shimbo, Yuji MatsumotoAbstract:Bootstrapping has a tendency, called semantic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of Espresso-style Bootstrapping has the same root as the topic drift of Kleinberg's HITS, using a simplified graph-based reformulation of Bootstrapping. We confirm that two graph-based algorithms, the von Neumann kernels and the regularized Laplacian, can reduce the effect of semantic drift in the task of word sense disambiguation (WSD) on Senseval-3 English Lexical Sample Task. Proposed algorithms achieve superior performance to Espresso and previous graph-based WSD methods, even though the proposed algorithms have less parameters and are easy to calibrate.
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graph based analysis of semantic drift in espresso like Bootstrapping algorithms
Empirical Methods in Natural Language Processing, 2008Co-Authors: Mamoru Komachi, Taku Kudo, Masashi Shimbo, Yuji MatsumotoAbstract:Bootstrapping has a tendency, called semantic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of Bootstrapping has the same root as the topic drift of Kleinberg's HITS, using a simplified graph-based reformulation of Bootstrapping. We confirm that two graph-based algorithms, the von Neumann kernels and the regularized Laplacian, can reduce semantic drift in the task of word sense disambiguation (WSD) on Senseval-3 English Lexical Sample Task. Proposed algorithms achieve superior performance to Espresso and previous graph-based WSD methods, even though the proposed algorithms have less parameters and are easy to calibrate.
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EMNLP - Graph-based Analysis of Semantic Drift in Espresso-like Bootstrapping Algorithms
Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08, 2008Co-Authors: Mamoru Komachi, Taku Kudo, Masashi Shimbo, Yuji MatsumotoAbstract:Bootstrapping has a tendency, called semantic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of Bootstrapping has the same root as the topic drift of Kleinberg's HITS, using a simplified graph-based reformulation of Bootstrapping. We confirm that two graph-based algorithms, the von Neumann kernels and the regularized Laplacian, can reduce semantic drift in the task of word sense disambiguation (WSD) on Senseval-3 English Lexical Sample Task. Proposed algorithms achieve superior performance to Espresso and previous graph-based WSD methods, even though the proposed algorithms have less parameters and are easy to calibrate.
Dmitry Chicherin - One of the best experts on this subject based on the ideXlab platform.
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Bootstrapping pentagon functions
Journal of High Energy Physics, 2018Co-Authors: Dmitry Chicherin, Johannes M. Henn, Vladimir MitevAbstract:In Phys. Rev. Lett. 116 (2016) 062001, the space of planar pentagon functions that describes all two-loop on-shell five-particle scattering amplitudes was introduced. In the present paper we present a natural extension of this space to non-planar pentagon functions. This provides the basis for our pentagon bootstrap program. We classify the relevant functions up to weight four, which is relevant for two-loop scattering amplitudes. We constrain the first entry of the symbol of the functions using information on branch cuts. Drawing on an analogy from the planar case, we introduce a conjectural second-entry condition on the symbol. We then show that the information on the function space, when complemented with some additional insights, can be used to efficiently bootstrap individual Feynman integrals. The extra information is read off of Mellin-Barnes representations of the integrals, either by evaluating simple asymptotic limits, or by taking discontinuities in the kinematic variables. We use this method to evaluate the symbols of two non-trivial non-planar five-particle integrals, up to and including the finite part.
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Bootstrapping pentagon functions
arXiv: High Energy Physics - Theory, 2017Co-Authors: Dmitry Chicherin, Johannes M. Henn, Vladimir MitevAbstract:In PRL 116 (2016) no.6, 062001, the space of planar pentagon functions that describes all two-loop on-shell five-particle scattering amplitudes was introduced. In the present paper we present a natural extension of this space to non-planar pentagon functions. This provides the basis for our pentagon bootstrap program. We classify the relevant functions up to weight four, which is relevant for two-loop scattering amplitudes. We constrain the first entry of the symbol of the functions using information on branch cuts. Drawing on an analogy from the planar case, we introduce a conjectural second-entry condition on the symbol. We then show that the information on the function space, when complemented with some additional insights, can be used to efficiently bootstrap individual Feynman integrals. The extra information is read off of Mellin-Barnes representations of the integrals, either by evaluating simple asymptotic limits, or by taking discontinuities in the kinematic variables. We use this method to evaluate the symbols of two non-trivial non-planar five-particle integrals, up to and including the finite part.