Handbook of Natural Language Processing最新文献_第2页

Emerging Applications of Natural Language Generation in Information Visualization, Education, and Health Care 自然语言生成在信息可视化、教育和医疗保健中的新兴应用

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c23

Barbara Maria Di Eugenio, N. Green

引用次数: 7

Multiword Expressions 多字表达式

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c12

Timothy Baldwin, Su Nam Kim

引用次数: 323

Word Sense Disambiguation 词义消歧

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c14

David Yarowsky

{"title":"Word Sense Disambiguation","authors":"David Yarowsky","doi":"10.1201/9781420085938-c14","DOIUrl":"https://doi.org/10.1201/9781420085938-c14","url":null,"abstract":"This paper describes a program that disambignates English word senses in unrestricted text using statistical models of the major Roget's Thesaurus categories. Roget's categories serve as approximations of conceptual classes. The categories listed for a word in Roger's index tend to correspond to sense distinctions; thus selecting the most likely category provides a useful level of sense disambiguatiou. The selection of categories is accomplished by identifying and weighting words that are indicative of each category when seen in context, using a Bayesian theoretical framework. Other statistical approaches have required special corpora or hand-labeled training examples for much of the lexicon. Our use of class models overcomes this knowledge acquisition bottleneck, enabling training on unresUicted monolingual text without human intervention. Applied to the 10 million word Grolier's Encyclopedia, the system correctly disambiguated 92% of the instances of 12 polysemous words that have been previously studied in the literature. 1. Problem Formulation This paper presents an approach to word sense disambiguation that uses classes of words to derive models useful for disambignating individual words in context. \"Sense\" is not a well defined concept; it has been based on subjective and often subtle distinctions in topic, register, dialect, collocation, part of speech and valency. For the purposes of this study, we will define the senses of a word as the categories listed for that word in Roger's International Thesaurus (Fourth Edition Chapman, 1977). 1 Sense disambiguation will constitute 1. Note that this edition of Roger's Thesaurus is much more e0ttm$ive than the 1911 vm'sion, though somewhat more difficult to obtain in electronic form, One could me other other concept hlemrehics, such as WordNet (Miller, 1990) or the LDOCE mbject codes (Slator, 1991). All that it necessary is • set of semamic categories and • list of the words in each category. selecting the listed category which is most probable given the surrounding context. This may appear to be a particularly crude approximation, but as shown in the example below and in the table of results, it is surprisingly successful.","PeriodicalId":361311,"journal":{"name":"Handbook of Natural Language Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129795705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Statistical Machine Translation 统计机器翻译

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c17

Abraham Ittycheriah

引用次数: 0

Report Generation 报告生成

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c22

E. Riloff, Leo Wanner

引用次数: 1

Alignment 对齐

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c16

Dekai Wu

引用次数: 57

Part-of-Speech Tagging 词性标注

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c10

Tunga Güngör

引用次数: 0

Statistical Parsing 统计分析

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c11

Joakim Nivre

引用次数: 18

Chinese Machine Translation 中文机器翻译

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c18

Pascale Fung

引用次数: 0

Information Extraction 信息提取

Handbook of Natural Language Processing Pub Date : 1900-01-01 DOI: 10.1201/9781420085938-c21

Jerry R. Hobbs

{"title":"Information Extraction","authors":"Jerry R. Hobbs","doi":"10.1201/9781420085938-c21","DOIUrl":"https://doi.org/10.1201/9781420085938-c21","url":null,"abstract":"Information Extraction (IE) techniques aim to extract the names of entities and objects from text and to identify the roles that they play in event descriptions. IE systems generally focus on a specific domain or topic, searching only for information that is relevant to a user's interests. In this chapter, we first give historical background on information extraction and discuss several kinds of information extraction tasks that have emerged in recent years. Next, we outline the series of steps that are involved in creating a typical information extraction system, which can be encoded as a cascaded finite-state transducer. Along the way, we present examples to illustrate what each step does. Finally, we present an overview of different learning-based methods for information extraction, including supervised learning approaches, weakly supervised and bootstrapping techniques, and discourse-oriented approaches. Information extraction (IE) is the process of scanning text for information relevant to some interest, including extracting entities, relations, and, most challenging, events–or who did what to whom when and where. It requires deeper analysis than key word searches, but its aims fall short of the very hard and long-term problem of text understanding, where we seek to capture all the information in a text, along with the speaker's or writer's intention.","PeriodicalId":361311,"journal":{"name":"Handbook of Natural Language Processing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116076630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0