This paper proposes a context-sensitive convolution tree kernel for pronoun resolution. It resolves two critical problems in previous researches in two ways. First, given a parse tree and a pair of an anaphor and an a...
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This paper proposes a semi-supervised learning method for relation extraction. Given a small amount of labeled data and a large amount of unlabeled data, it first bootstraps a moderate number of weighted support vecto...
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This paper proposes a new approach to dynamically determine the tree span for tree kernel-based semantic relation extraction. It exploits constituent dependencies to keep the nodes and their head children along the pa...
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This paper proposes a dependency tree-based SRL system with proper pruning and extensive feature engineering. Official evaluation on the CoNLL 2008 shared task shows that our system achieves 76.19 in labeled macro F1 ...
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SIFT (Scale Invariant Feature Transform) is used to solve visual tracking problem, where the appearances of the tracked object and scene background change during tracking. The implementation of this algorithm has five...
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This paper mainly presents two approaches for image retrieval. There is some faintness in color locating in quantification boundary when image color is quantized. The membership function in fuzzy set theory can descri...
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This paper explores the contributions of various features in semantic role labeling. Moreover, an optimal set of features is selected using a greedy strategy. Finally, an effective headword-driven pruning algorithm is...
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This paper explores the contributions of various features in semantic role labeling. Moreover, an optimal set of features is selected using a greedy strategy. Finally, an effective headword-driven pruning algorithm is proposed to filter out irrelavant instances. Evaluation on the CoNLL'2005 SRL benchmark corpus shows that our method achieved comparable performance with the best-reported ones on a single automatic parse tree.
An increasing number of databases have become Web accessible through HTML form-based search interfaces, which is so-called deep Web. For full utilization of deep Web resources and improving Web intelligence, which is ...
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An increasing number of databases have become Web accessible through HTML form-based search interfaces, which is so-called deep Web. For full utilization of deep Web resources and improving Web intelligence, which is essential for many applications such as deep Web data collection and comparison shopping, they need to be extracted out and assigned meaningful labels. In this paper, we present a synchronous-annotation approach that introduce domain ontology as a global schema ordered by Web databases to the annotation process. We combine ontology, interface schema and result schema and adopt the strategy of query ontology instance to implement annotation. In order to verify the effectiveness of the method proposed in this paper, we test on a number of different areas of Web databases. The experimental results indicate that the proposed approach is more effective than existing approaches.
This paper proposes a unified dynamic relation tree (DRT) span for tree kernel-based semantic relation extraction between entity names. The basic idea is to apply a variety of linguistics-driven rules to dynamically p...
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This paper proposes a unified dynamic relation tree (DRT) span for tree kernel-based semantic relation extraction between entity names. The basic idea is to apply a variety of linguistics-driven rules to dynamically prune out noisy information from a syntactic parse tree and include necessary contextual information. In addition, different kinds of entity-related semantic information are unified into the syntactic parse tree. Evaluation on the ACE RDC 2004 corpus shows that the unified DRT span outperforms other widely-used tree spans, and our system achieves comparable performance with the state-of-the-art kernel-based ones. This indicates that our method can not only well model the structured syntactic information but also effectively capture entity-related semantic information.
With the startup of the Golden Agriculture Project, the step of being-information of agriculture is becoming rapid. And the transformation and share of data is indispensable to the being-information of agriculture. Ho...
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With the startup of the Golden Agriculture Project, the step of being-information of agriculture is becoming rapid. And the transformation and share of data is indispensable to the being-information of agriculture. How to implement data combination, data transformation and data receiving applications are the important means to complete the information share safely and enhance the efficiency. The paper starts with searching of methods to implement data interchange, and introduce some of the methods, points of the techniques, etc. Basing on this, the paper also introduces the detail requirement analyses, system design and detail implementation of the system. According to the requirement and trait of the project, a data interchange system is researched and completed. And a data interchange model based on message-oriented middleware (MOM) is presented in this paper, which builds a middleware between the province and the ministry taking part in data interchange. The system has traits as follows: 1. keeping the data safe and credible while it is transformed. 2. having excellent transplantable and applied capability. 3. doesn't need intervention of workman in the process of data interchange. 4. applying the data interchange between databases of different structure. 5. being simple to be developed and applied. MOM TongLink/Q offers interfaces for application development, and it completes the data transformation through the internet. The integration adapters developed do the data management, which are developed based on the Frame for Applications Integration TongIntegrator. This method offers a new approach to resolve the question of data interchange. Now the system has been successfully applied in the data interchange project of Ministry of Agriculture.
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