{"title":"基于最近邻算法的句子实现从阶乘到二次时间复杂度","authors":"Karthik Gali, Sriram Venkatapathy, Taraka Rama","doi":"10.1109/STIL.2009.38","DOIUrl":null,"url":null,"abstract":"{karthikg@students,sriram@research,taraka@students}.iiit.ac.in Abstract. Sentence Realization is the task of generating a well-formed sentence from a bag of words. Sentence Realization is a major step in many Natural Language Processing applications like Machine Translation (MT), Summariza- tion and Dialogue Systems. In this paper, we explore a graph based Nearest Neighbour Algorithm for the task of Sentence Realization. Sentence Realization is a major step in many Natural Language Processing applications like Machine Translation (MT), Summarization and Dialogue Systems. The task of Sen- tence Realization involves formation of a well-formed sentence from a bag of lexical items. These lexical items may be attached syntactically with one another. The level of syntactic information varies from application to application. Our aim consists of achiev- ing quality sentence realiser using as much as minimum syntactic information and of minimal computational complexity. As such our experiments assume only basic syntactic information, such as unlabeled dependency relationships between the lexical items. Graph based algorithms for Natural Language applications such as Pars- ing (McDonald et al. 2005), Summarization (Mihalcea and Tarau 2005) and Word sense disambiguation (Mihalcea 2005) have been well explored. For the task of Sentence Re- alization, graph based algorithms have yet to be explored. This paper is a novel effort in that direction.","PeriodicalId":265848,"journal":{"name":"2009 Seventh Brazilian Symposium in Information and Human Language Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"From Factorial to Quadratic Time Complexity for Sentence Realization Using Nearest Neighbour Algorithm\",\"authors\":\"Karthik Gali, Sriram Venkatapathy, Taraka Rama\",\"doi\":\"10.1109/STIL.2009.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"{karthikg@students,sriram@research,taraka@students}.iiit.ac.in Abstract. Sentence Realization is the task of generating a well-formed sentence from a bag of words. Sentence Realization is a major step in many Natural Language Processing applications like Machine Translation (MT), Summariza- tion and Dialogue Systems. In this paper, we explore a graph based Nearest Neighbour Algorithm for the task of Sentence Realization. Sentence Realization is a major step in many Natural Language Processing applications like Machine Translation (MT), Summarization and Dialogue Systems. The task of Sen- tence Realization involves formation of a well-formed sentence from a bag of lexical items. These lexical items may be attached syntactically with one another. The level of syntactic information varies from application to application. Our aim consists of achiev- ing quality sentence realiser using as much as minimum syntactic information and of minimal computational complexity. As such our experiments assume only basic syntactic information, such as unlabeled dependency relationships between the lexical items. Graph based algorithms for Natural Language applications such as Pars- ing (McDonald et al. 2005), Summarization (Mihalcea and Tarau 2005) and Word sense disambiguation (Mihalcea 2005) have been well explored. For the task of Sentence Re- alization, graph based algorithms have yet to be explored. This paper is a novel effort in that direction.\",\"PeriodicalId\":265848,\"journal\":{\"name\":\"2009 Seventh Brazilian Symposium in Information and Human Language Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Seventh Brazilian Symposium in Information and Human Language Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STIL.2009.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Seventh Brazilian Symposium in Information and Human Language Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STIL.2009.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
{karthikg@students, sriram@research, taraka@students} .iiit.ac。在抽象的。句子实现的任务是从一堆单词中生成一个格式良好的句子。句子实现是许多自然语言处理应用的一个重要步骤,如机器翻译、摘要和对话系统。在本文中,我们探索了一种基于图的最近邻算法来完成句子实现任务。句子实现是许多自然语言处理应用的重要步骤,如机器翻译、摘要和对话系统。句子实现的任务包括从一袋词汇项目中形成一个结构良好的句子。这些词法项可以在语法上相互连接。语法信息的级别因应用程序而异。我们的目标是使用最少的句法信息和最少的计算复杂度来实现高质量的句子实现器。因此,我们的实验只假设基本的句法信息,如词法项之间未标记的依赖关系。自然语言应用的基于图的算法,如解析(McDonald et al. 2005)、摘要(Mihalcea and Tarau 2005)和词义消歧(Mihalcea 2005)已经得到了很好的探索。对于句子再表示的任务,基于图的算法还有待探索。这篇论文是在这个方向上的一个新颖的尝试。
From Factorial to Quadratic Time Complexity for Sentence Realization Using Nearest Neighbour Algorithm
{karthikg@students,sriram@research,taraka@students}.iiit.ac.in Abstract. Sentence Realization is the task of generating a well-formed sentence from a bag of words. Sentence Realization is a major step in many Natural Language Processing applications like Machine Translation (MT), Summariza- tion and Dialogue Systems. In this paper, we explore a graph based Nearest Neighbour Algorithm for the task of Sentence Realization. Sentence Realization is a major step in many Natural Language Processing applications like Machine Translation (MT), Summarization and Dialogue Systems. The task of Sen- tence Realization involves formation of a well-formed sentence from a bag of lexical items. These lexical items may be attached syntactically with one another. The level of syntactic information varies from application to application. Our aim consists of achiev- ing quality sentence realiser using as much as minimum syntactic information and of minimal computational complexity. As such our experiments assume only basic syntactic information, such as unlabeled dependency relationships between the lexical items. Graph based algorithms for Natural Language applications such as Pars- ing (McDonald et al. 2005), Summarization (Mihalcea and Tarau 2005) and Word sense disambiguation (Mihalcea 2005) have been well explored. For the task of Sentence Re- alization, graph based algorithms have yet to be explored. This paper is a novel effort in that direction.