Language resources, including corpus and tools, are normally required to be combined in order to ... more Language resources, including corpus and tools, are normally required to be combined in order to achieve a user's specific task. However, resources tend to be developed independently in different, incompatible formats. In this paper we describe about U-Compare, which consists of the U-Compare component repository and the U-Compare platform. We have been building a highly interoperable resource library, providing the world largest ready-to-use UIMA component repository including wide variety of corpus readers and state-of-the-art language tools. These resources can be deployed as local services or web services, even possible to be hosted in clustered machines to increase the performance, while users do not need to be aware of such differences. In addition to the resource library, an integrated language processing platform is provided, allowing workflow creation, comparison, evaluation and visualization, using the resources in the library or any UIMA component, without any programming via graphical user interfaces, while a command line launcher is also available without GUIs. The evaluation itself is processed in a UIMA component, users can create and plug their own evaluation metrics in addition to the predefined metrics. U-Compare has been successfully used in many projects including BioCreative, Conll and the BioNLP shared task.
Computational modeling is an important tool in the study of language evolution. It is not only us... more Computational modeling is an important tool in the study of language evolution. It is not only used to test hypotheses, but also as a source of data on difficult to observe evolutionary dynamics. This makes it particularly important to distinguish the emergent behaviors of evolutionary systems being studied, from the behaviors of specific models. In this paper we provide an in-depth analysis of one recent model of linguistic bio-cultural coevolution (Yamauchi & Hashimoto 2010) and show that several of its reported behaviors are artifacts produced by the model’s design and parameter settings. Specifically, we show that the model’s population size setting and agent “geography” place strong limits on both cultural and biological diversity in the model. These limits interact with the model’s learning mechanism and result in a number of semi-stable attractor states. We argue that it is the proper- ties of these attractors that account for the long run behavior of the model, directly conflicting with the analysis given in the original paper. Our results are confirmed by experiments altering the model’s population size parameter which result in a qualitative change in the observed model behavior.
Language resources, including corpus and tools, are normally required to be combined in order to ... more Language resources, including corpus and tools, are normally required to be combined in order to achieve a user's specific task. However, resources tend to be developed independently in different, incompatible formats. In this paper we describe about U-Compare, which consists of the U-Compare component repository and the U-Compare platform. We have been building a highly interoperable resource library, providing the world largest ready-to-use UIMA component repository including wide variety of corpus readers and state-of-the-art language tools. These resources can be deployed as local services or web services, even possible to be hosted in clustered machines to increase the performance, while users do not need to be aware of such differences. In addition to the resource library, an integrated language processing platform is provided, allowing workflow creation, comparison, evaluation and visualization, using the resources in the library or any UIMA component, without any programming via graphical user interfaces, while a command line launcher is also available without GUIs. The evaluation itself is processed in a UIMA component, users can create and plug their own evaluation metrics in addition to the predefined metrics. U-Compare has been successfully used in many projects including BioCreative, Conll and the BioNLP shared task.
Computational modeling is an important tool in the study of language evolution. It is not only us... more Computational modeling is an important tool in the study of language evolution. It is not only used to test hypotheses, but also as a source of data on difficult to observe evolutionary dynamics. This makes it particularly important to distinguish the emergent behaviors of evolutionary systems being studied, from the behaviors of specific models. In this paper we provide an in-depth analysis of one recent model of linguistic bio-cultural coevolution (Yamauchi & Hashimoto 2010) and show that several of its reported behaviors are artifacts produced by the model’s design and parameter settings. Specifically, we show that the model’s population size setting and agent “geography” place strong limits on both cultural and biological diversity in the model. These limits interact with the model’s learning mechanism and result in a number of semi-stable attractor states. We argue that it is the proper- ties of these attractors that account for the long run behavior of the model, directly conflicting with the analysis given in the original paper. Our results are confirmed by experiments altering the model’s population size parameter which result in a qualitative change in the observed model behavior.
Uploads
Papers by Luke McCrohon