The Experts below are selected from a list of 11004 Experts worldwide ranked by ideXlab platform
Roberto Navigli - One of the best experts on this subject based on the ideXlab platform.
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a unified multilingual Semantic Representation of concepts
International Joint Conference on Natural Language Processing, 2015Co-Authors: Jose Camachocollados, Mohammad Taher Pilehvar, Roberto NavigliAbstract:Semantic Representation lies at the core of several applications in Natural Language Processing. However, most existing Semantic Representation techniques cannot be used effectively for the Representation of individual word senses. We put forward a novel multilingual concept Representation, called MUFFIN, which not only enables accurate Representation of word senses in different languages, but also provides multiple advantages over existing approaches. MUFFIN represents a given concept in a unified Semantic space irrespective of the language of interest, enabling cross-lingual comparison of different concepts. We evaluate our approach in two different evaluation benchmarks, Semantic similarity and Word Sense Disambiguation, reporting state-of-the-art performance on several standard datasets.
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ACL (1) - A Unified Multilingual Semantic Representation of Concepts
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language, 2015Co-Authors: Jose Camacho-collados, Mohammad Taher Pilehvar, Roberto NavigliAbstract:Semantic Representation lies at the core of several applications in Natural Language Processing. However, most existing Semantic Representation techniques cannot be used effectively for the Representation of individual word senses. We put forward a novel multilingual concept Representation, called MUFFIN, which not only enables accurate Representation of word senses in different languages, but also provides multiple advantages over existing approaches. MUFFIN represents a given concept in a unified Semantic space irrespective of the language of interest, enabling cross-lingual comparison of different concepts. We evaluate our approach in two different evaluation benchmarks, Semantic similarity and Word Sense Disambiguation, reporting state-of-the-art performance on several standard datasets.
Yingzhong Zhang - One of the best experts on this subject based on the ideXlab platform.
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LCA-oriented Semantic Representation for the product life cycle
Journal of Cleaner Production, 2015Co-Authors: Yingzhong Zhang, Xiaofang Luo, Jennifer J. Buis, John W. SutherlandAbstract:In order to complete a life cycle assessment (LCA) study of the product, each activity interacting with the environment during the product life cycle should be given an explicit description, namely an LCA-oriented Representation for the product life cycle should be constructed. A complex functional product usually consists of many parts made of different materials and its LCA-oriented life cycle modeling involves many complex Semantic relationships. In this paper, a new LCA-oriented and ontology-based Semantic Representation model and methodology for the product life cycle are proposed. First, the concepts of processes and flows, and the Semantic relationships among processes, and between processes and flows are analyzed in detail. The ontology classes of processes and flows are defined using the Web Ontology Language (OWL). Then, an LCA-oriented Semantic concept model for the product life cycle is presented. Based on the proposed Semantic Representation model, all processes, flows, and the relationships among them can be represented as a Resource Description Framework (RDF) graph in which each node is an instance tagged by an ontology class. A formalization of lifecycle processes on flows is provided, which can be encoded with Semantic Web Rule Language (SWRL) and formed into a knowledge rule base. In addition, a Semantic query method for the life cycle inventory of a product is proposed. Finally, an implementation framework and an example of the Semantic Representation for a ball bearing's life cycle are provided.
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A Semantic Representation model for design rationale of products
Advanced Engineering Informatics, 2013Co-Authors: Yingzhong Zhang, Xiaofang Luo, Jian Li, Jennifer J. BuisAbstract:Design rationale (DR) is crucial information in product design decision support, design analysis and design reuse. In this paper, based on the Issue-based Information System (IBIS) model, a new ontology-based Semantic Representation model for DR information; the integrated issue, solution, artifact and argument (ISAA) model; is proposed. The ISAA model introduces the ontology-based Semantic Representation mode to the DR Representation and expands the concept elements of IBIS. The class of concept elements and the Semantic relationships among them are defined by Web Ontology Language (OWL). The axioms and rules which are used to reason and analyze DR are defined and encoded with Semantic Web Rule Language (SWRL), which enrich the Semantic relations defined by OWL. The ISAA model represents the directed graph of IBIS to the Resource Description Framework (RDF) graph and serializes to an RDF/XML document which lays the foundation for retrieving and reasoning Semantic information of DR. A Semantic annotator integrating with the visual product design model was developed, by which the discrete information of thinking is captured and abstracted to a conceptual Representation of the ISAA model. Finally, an example of DR Representation for the spring operating mechanism of a high-voltage circuit breaker product is given. © 2012 Elsevier Ltd. All rights reserved.
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a Semantic Representation model for design rationale of products
Advanced Engineering Informatics, 2013Co-Authors: Yingzhong Zhang, Jian Li, Jennifer J. BuisAbstract:Design rationale (DR) is crucial information in product design decision support, design analysis and design reuse. In this paper, based on the Issue-based Information System (IBIS) model, a new ontology-based Semantic Representation model for DR information; the integrated issue, solution, artifact and argument (ISAA) model; is proposed. The ISAA model introduces the ontology-based Semantic Representation mode to the DR Representation and expands the concept elements of IBIS. The class of concept elements and the Semantic relationships among them are defined by Web Ontology Language (OWL). The axioms and rules which are used to reason and analyze DR are defined and encoded with Semantic Web Rule Language (SWRL), which enrich the Semantic relations defined by OWL. The ISAA model represents the directed graph of IBIS to the Resource Description Framework (RDF) graph and serializes to an RDF/XML document which lays the foundation for retrieving and reasoning Semantic information of DR. A Semantic annotator integrating with the visual product design model was developed, by which the discrete information of thinking is captured and abstracted to a conceptual Representation of the ISAA model. Finally, an example of DR Representation for the spring operating mechanism of a high-voltage circuit breaker product is given.
Mirella Lapata - One of the best experts on this subject based on the ideXlab platform.
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grounded models of Semantic Representation
Empirical Methods in Natural Language Processing, 2012Co-Authors: Carina Silberer, Mirella LapataAbstract:A popular tradition of studying Semantic Representation has been driven by the assumption that word meaning can be learned from the linguistic environment, despite ample evidence suggesting that language is grounded in perception and action. In this paper we present a comparative study of models that represent word meaning based on linguistic and perceptual data. Linguistic information is approximated by naturally occurring corpora and sensorimotor experience by feature norms (i.e., attributes native speakers consider important in describing the meaning of a word). The models differ in terms of the mechanisms by which they integrate the two modalities. Experimental results show that a closer correspondence to human data can be obtained by uncovering latent information shared among the textual and perceptual modalities rather than arriving at Semantic knowledge by concatenating the two.
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visual information in Semantic Representation
North American Chapter of the Association for Computational Linguistics, 2010Co-Authors: Yansong Feng, Mirella LapataAbstract:The question of how meaning might be acquired by young children and represented by adult speakers of a language is one of the most debated topics in cognitive science. Existing Semantic Representation models are primarily amodal based on information provided by the linguistic input despite ample evidence indicating that the cognitive system is also sensitive to perceptual information. In this work we exploit the vast resource of images and associated documents available on the web and develop a model of multimodal meaning Representation which is based on the linguistic and visual context. Experimental results show that a closer correspondence to human data can be obtained by taking the visual modality into account.
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HLT-NAACL - Visual Information in Semantic Representation
2010Co-Authors: Yansong Feng, Mirella LapataAbstract:The question of how meaning might be acquired by young children and represented by adult speakers of a language is one of the most debated topics in cognitive science. Existing Semantic Representation models are primarily amodal based on information provided by the linguistic input despite ample evidence indicating that the cognitive system is also sensitive to perceptual information. In this work we exploit the vast resource of images and associated documents available on the web and develop a model of multimodal meaning Representation which is based on the linguistic and visual context. Experimental results show that a closer correspondence to human data can be obtained by taking the visual modality into account.
Jennifer J. Buis - One of the best experts on this subject based on the ideXlab platform.
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LCA-oriented Semantic Representation for the product life cycle
Journal of Cleaner Production, 2015Co-Authors: Yingzhong Zhang, Xiaofang Luo, Jennifer J. Buis, John W. SutherlandAbstract:In order to complete a life cycle assessment (LCA) study of the product, each activity interacting with the environment during the product life cycle should be given an explicit description, namely an LCA-oriented Representation for the product life cycle should be constructed. A complex functional product usually consists of many parts made of different materials and its LCA-oriented life cycle modeling involves many complex Semantic relationships. In this paper, a new LCA-oriented and ontology-based Semantic Representation model and methodology for the product life cycle are proposed. First, the concepts of processes and flows, and the Semantic relationships among processes, and between processes and flows are analyzed in detail. The ontology classes of processes and flows are defined using the Web Ontology Language (OWL). Then, an LCA-oriented Semantic concept model for the product life cycle is presented. Based on the proposed Semantic Representation model, all processes, flows, and the relationships among them can be represented as a Resource Description Framework (RDF) graph in which each node is an instance tagged by an ontology class. A formalization of lifecycle processes on flows is provided, which can be encoded with Semantic Web Rule Language (SWRL) and formed into a knowledge rule base. In addition, a Semantic query method for the life cycle inventory of a product is proposed. Finally, an implementation framework and an example of the Semantic Representation for a ball bearing's life cycle are provided.
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A Semantic Representation model for design rationale of products
Advanced Engineering Informatics, 2013Co-Authors: Yingzhong Zhang, Xiaofang Luo, Jian Li, Jennifer J. BuisAbstract:Design rationale (DR) is crucial information in product design decision support, design analysis and design reuse. In this paper, based on the Issue-based Information System (IBIS) model, a new ontology-based Semantic Representation model for DR information; the integrated issue, solution, artifact and argument (ISAA) model; is proposed. The ISAA model introduces the ontology-based Semantic Representation mode to the DR Representation and expands the concept elements of IBIS. The class of concept elements and the Semantic relationships among them are defined by Web Ontology Language (OWL). The axioms and rules which are used to reason and analyze DR are defined and encoded with Semantic Web Rule Language (SWRL), which enrich the Semantic relations defined by OWL. The ISAA model represents the directed graph of IBIS to the Resource Description Framework (RDF) graph and serializes to an RDF/XML document which lays the foundation for retrieving and reasoning Semantic information of DR. A Semantic annotator integrating with the visual product design model was developed, by which the discrete information of thinking is captured and abstracted to a conceptual Representation of the ISAA model. Finally, an example of DR Representation for the spring operating mechanism of a high-voltage circuit breaker product is given. © 2012 Elsevier Ltd. All rights reserved.
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a Semantic Representation model for design rationale of products
Advanced Engineering Informatics, 2013Co-Authors: Yingzhong Zhang, Jian Li, Jennifer J. BuisAbstract:Design rationale (DR) is crucial information in product design decision support, design analysis and design reuse. In this paper, based on the Issue-based Information System (IBIS) model, a new ontology-based Semantic Representation model for DR information; the integrated issue, solution, artifact and argument (ISAA) model; is proposed. The ISAA model introduces the ontology-based Semantic Representation mode to the DR Representation and expands the concept elements of IBIS. The class of concept elements and the Semantic relationships among them are defined by Web Ontology Language (OWL). The axioms and rules which are used to reason and analyze DR are defined and encoded with Semantic Web Rule Language (SWRL), which enrich the Semantic relations defined by OWL. The ISAA model represents the directed graph of IBIS to the Resource Description Framework (RDF) graph and serializes to an RDF/XML document which lays the foundation for retrieving and reasoning Semantic information of DR. A Semantic annotator integrating with the visual product design model was developed, by which the discrete information of thinking is captured and abstracted to a conceptual Representation of the ISAA model. Finally, an example of DR Representation for the spring operating mechanism of a high-voltage circuit breaker product is given.
Shinji Nishimoto - One of the best experts on this subject based on the ideXlab platform.
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SMC - Semantic Representation in the cerebral cortex with sparse coding
2017 IEEE International Conference on Systems Man and Cybernetics (SMC), 2017Co-Authors: Chiaki Kawase, Ichiro Kobayashi, Shinji Nishimoto, Satoshi Nishida, Hideki AsohAbstract:In this study, we investigate whether sparse coding helps explain the Semantic Representation in human cerebral cortex. We show this by using sparse coding to model Semantic Representation in the cerebral cortex. We propose three methods for estimating Semantic Representation from brain activity data. For estimating a new Semantic Representation, in the first method, we use only a Semantic Representation dictionary obtained via sparse coding. The Semantic Representation estimated using this method is more similar to the actual Semantic Representation of the cerebral cortex than that estimated without sparse coding. In the second method, we use only a brain activity dictionary obtained via sparse coding. The Semantic Representation estimated using this method is also better than that estimated without sparse coding. In addition, in the third method, we estimate Semantic Representation by applying sparse coding to both Semantic Representation and brain activity data. The Semantic Representation estimated by using this third method is better than that estimated by the first or second methods. Through the above three experiments, we have confirmed that sparse coding helps explain the Semantic Representation in human cerebral cortex.
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Semantic Representation in the cerebral cortex with sparse coding
2017 IEEE International Conference on Systems Man and Cybernetics (SMC), 2017Co-Authors: Chiaki Kawase, Ichiro Kobayashi, Shinji Nishimoto, Satoshi Nishida, Hideki AsohAbstract:In this study, we investigate whether sparse coding helps explain the Semantic Representation in human cerebral cortex. We show this by using sparse coding to model Semantic Representation in the cerebral cortex. We propose three methods for estimating Semantic Representation from brain activity data. For estimating a new Semantic Representation, in the first method, we use only a Semantic Representation dictionary obtained via sparse coding. The Semantic Representation estimated using this method is more similar to the actual Semantic Representation of the cerebral cortex than that estimated without sparse coding. In the second method, we use only a brain activity dictionary obtained via sparse coding. The Semantic Representation estimated using this method is also better than that estimated without sparse coding. In addition, in the third method, we estimate Semantic Representation by applying sparse coding to both Semantic Representation and brain activity data. The Semantic Representation estimated by using this third method is better than that estimated by the first or second methods. Through the above three experiments, we have confirmed that sparse coding helps explain the Semantic Representation in human cerebral cortex.
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attention during natural vision warps Semantic Representation across the human brain
Nature Neuroscience, 2013Co-Authors: Tolga Çukur, Shinji Nishimoto, Alexander G Huth, Jack L GallantAbstract:The authors use functional magnetic resonance imaging to measure how the Semantic Representation changes when searching for different object categories in natural movies. They find tuning shifts that expand the Representation of the attended category and of Semantically related, but unattended, categories, and compress the Representation of categories Semantically dissimilar to the target.
