检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

105 册 图书

馆藏范围

105 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

41 篇 工学
- 29 篇 计算机科学与技术...
- 18 篇 控制科学与工程
- 9 篇 软件工程
16 篇 理学
- 16 篇 系统科学
6 篇 管理学
- 5 篇 管理科学与工程(可...
- 1 篇 图书情报与档案管...
4 篇 文学
- 2 篇 中国语言文学
- 2 篇 外国语言文学
2 篇 法学
- 2 篇 社会学

主题

61 篇 artificial intel...
58 篇 natural language...
56 篇 computational li...
8 篇 machine learning
6 篇 language
5 篇 computer science
5 篇 computer science...
5 篇 synthesis
5 篇 lectures
4 篇 human
4 篇 computers
3 篇 natural language...
3 篇 natural language...
3 篇 computer \u0026 ...
3 篇 natural
3 篇 processing
3 篇 human language t...
2 篇 knowledge based ...
2 篇 information scie...
2 篇 computer applica...

机构

5 篇 university of ot...
4 篇 university of co...
4 篇 university of he...
4 篇 university of po...
4 篇 microsoft resear...
4 篇 university of wa...
3 篇 university of ed...
3 篇 educational test...
2 篇 university of ed...
2 篇 tilburg universi...
2 篇 dataminr inc.
2 篇 pearson knowledg...
2 篇 university of mo...
2 篇 university of il...
2 篇 heidelberg unive...
2 篇 university of wa...
2 篇 nantes universit...
2 篇 montclair state ...
2 篇 university of so...
2 篇 university of ca...

作者

4 篇 diana inkpen
4 篇 shay cohen
3 篇 emily m. bender
3 篇 michael mctear
3 篇 preslav nakov
3 篇 anders søgaard
3 篇 jimmy lin
3 篇 hang li
3 篇 stan szpakowicz
3 篇 vivi nastase
3 篇 michael hagmann
3 篇 stefan riezler
2 篇 martin chodorow
2 篇 diarmuid ó séagd...
2 篇 lotem peled-cohe...
2 篇 chodorow martin
2 篇 rodrigo nogueira
2 篇 shashi narayan
2 篇 stede manfred
2 篇 atefeh farzindar

语言

92 篇 英文
13 篇 中文

检索条件"丛书名=Synthesis Lectures on Human Language Technologies"

共 105 条记录，以下是21-30 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Natural language Processing for Social Media

引用

丛书名： synthesis lectures on human language technologies

2015年

作者： Farzindar, Atefeh Inkpen, Diana

ISBN: (纸本)9781627053891;1627053891

This book presents the state-of-the-art in research and empirical studies in the field of Natural language Processing (NLP) for the semantic analysis of social media data. Over the past few years, online social networking sites have revolutionized the way we communicate with individuals, groups and communities, and altered everyday practices. The unprecedented volume and variety of user-generated content and the user interaction network constitute new opportunities for understanding social behavior and building socially intelligent systems. Much research work on social networks and the mining of the social web is based on graph theory. That is apt because a social structure is made up of a set of social actors and a set of the dyadic ties between these actors. We believe that the graph-mining methods for structure, information diffusion or influence spread in social networks needs to combined with the content analysis of social media. This provides the opportunity for new applications that use the information publicly available as a result of social interactions. The intended audience of this book is researchers who are interested in developing tools and applications for automatic analysis of social media texts. We assume that the readers have basic knowledge in the area of natural language processing and machine learning. This book will help the readers better understand computational linguistics and social media analysis, in particular text-mining techniques and NLP applications (such as summarization, localization detection, sentiment and emotion analysis, topic detection and machine translation) designed specifically for social media texts.

关键词： lectures human langua synthesis media language processing social natural

来源：评论

学校读者我要写书评

暂无评论

Automatic Detection of Verbal Deception

引用

丛书名： synthesis lectures on human language technologies

2015年

作者： Fitzpatrick, Eileen Bachenko, Joan Fornaciari, Tommaso

ISBN: (数字)9781627053389

ISBN: (纸本)9781627053372

The attempt to spot deception through its correlates in human behavior has a long history. Until recently, these efforts have concentrated on identifying individual "cues" that might occur with deception. However, with the advent of computational means to analyze language and other human behavior, we now have the ability to determine whether there are consistent clusters of differences in behavior that might be associated with a false statement as opposed to a true one. While its focus is on verbal behavior, this book describes a range of behaviors hysiological, gestural as well as verbal that have been proposed as indicators of deception. An overview of the primary psychological and cognitive theories that have been offered as explanations of deceptive behaviors gives context for the description of specific behaviors. The book also addresses the differences between data collected in a laboratory and "real-world" data with respect to the emotional and cognitive state of the liar. It discusses sources of real-world data and problematic issues in its collection and identifies the primary areas in which applied studies based on real-world data are critical, including police, security, border crossing, customs, and asylum interviews; congressional hearings; financial reporting; legal depositions; human resource evaluation; predatory communications that include Internet scams, identity theft, and fraud; and false product reviews. Having established the background, this book concentrates on computational analyses of deceptive verbal behavior that have enabled the field of deception studies to move from individual cues to overall differences in behavior. The computational work is organized around the features used for classification from ??-gram through syntax to predicate-argument and rhetorical structure. The book concludes with a set of open questions that the computational work has generated.

关键词： Natural language \u0026 Machine Translation

来源：评论

学校读者我要写书评

暂无评论

Linked Lexical Knowledge Bases: Foundations and Applications

引用

丛书名： synthesis lectures on human language technologies

2016年

作者： Gurevych, Iryna Eckle-Kohler, Judith Matuschek, Michael

ISBN: (数字)9781627059046

ISBN: (纸本)9781627059749

This book conveys the fundamentals of Linked Lexical Knowledge Bases (LLKB) and sheds light on their different aspects from various perspectives, focusing on their construction and use in natural language processing (NLP). It characterizes a wide range of both expert-based and collaboratively constructed lexical knowledge bases. Only basic familiarity with NLP is required and this book has been written for both students and researchers in NLP and related fields who are interested in knowledge-based approaches to language analysis and their applications. Lexical Knowledge Bases (LKBs) are indispensable in many areas of natural language processing, as they encode human knowledge of language in machine readable form, and as such, they are required as a reference when machines attempt to interpret natural language in accordance with human perception. In recent years, numerous research efforts have led to the insight that to make the best use of available knowledge, the orchestrated exploitation of different LKBs is necessary. This allows us to not only extend the range of covered words and senses, but also gives us the opportunity to obtain a richer knowledge representation when a particular meaning of a word is covered in more than one resource. Examples where such an orchestrated usage of LKBs proved beneficial include word sense disambiguation, semantic role labeling, semantic parsing, and text classification. This book presents different kinds of automatic, manual, and collaborative linkings between LKBs. A special chapter is devoted to the linking algorithms employing text-based, graph-based, and joint modeling methods. Following this, it presents a set of higher-level NLP tasks and algorithms, effectively utilizing the knowledge in LLKBs. Among them, you will find advanced methods, e.g., distant supervision, or continuous vector space models of knowledge bases (KB), that have become widely used at the time of this book's writing. Finally, multilingual applicatio

关键词： Information Retrieval

来源：评论

学校读者我要写书评

暂无评论

Introduction to Chinese Natural language Processing (synthesis lectures on human language technologies)

引用

丛书名： synthesis lectures on human language technologies

2009年

作者： Kam-Fai Wong Wenji Li Ruifeng Xu Zheng-sheng Zhang

ISBN: (数字)9781598299335

ISBN: (纸本)9781598299328

This book introduces Chinese language-processing issues and techniques to readers who already have a basic background in natural language processing (NLP). Since the major difference between Chinese and Western languages is at the word level, the book primarily focuses on Chinese morphological analysis and introduces the concept, structure, and interword semantics of Chinese words. The following topics are covered: a general introduction to Chinese NLP; Chinese characters, morphemes, and words and the characteristics of Chinese words that have to be considered in NLP applications; Chinese word segmentation; unknown word detection; word meaning and Chinese linguistic resources; interword semantics based on word collocation and NLP techniques for collocation extraction. Table of Contents: Introduction / Words in Chinese / Challenges in Chinese Morphological Processing / Chinese Word Segmentation / Unknown Word Identification / Word Meaning / Chinese Collocations / Automatic Chinese Collocation Extraction / Appendix / References / Author Biographies

关键词： Computers amp the Internet Natural language Processing

来源：评论

学校读者我要写书评

暂无评论

Bayesian Analysis in Natural language Processing

引用

丛书名： synthesis lectures on human language technologies 35

2016年

作者： Shay Cohen

ISBN: (纸本)1627058737;9781627058735;9781627054218;1627054219

Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis.

关键词： Natural language processing (Computer science) Bayesian statistical decision theory

来源：评论

学校读者我要写书评

暂无评论

Grammatical Inference for Computational Linguistics

引用

丛书名： synthesis lectures on human language technologies

2015年

作者： Heinz, Jeffrey de la Higuera, Colin van Zaanen, Menno

ISBN: (数字)9781608459780

ISBN: (纸本)9781608459773

This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally sound algorithms that learn structure from strings of symbols. The relationship to computational linguistics is natural because many research problems in computational linguistics are learning problems on words, phrases, and sentences: What algorithm can take as input some finite amount of data (for instance a corpus, annotated or otherwise) and output a system that behaves "correctly" on specific tasks? Throughout the text, the key concepts of grammatical inference are interleaved with illustrative examples drawn from problems in computational linguistics. Special attention is paid to the notion of "learning bias." In the context of computational linguistics, such bias can be thought to reflect common (ideally universal) properties of natural languages. This bias can be incorporated either by identifying a learnable class of languages which contains the language to be learned or by using particular strategies for optimizing parameter values. Examples are drawn largely from two linguistic domains (phonology and syntax) which span major regions of the Chomsky Hierarchy (from regular to context-sensitive classes). The conclusion summarizes the major lessons and open questions that grammatical inference brings to computational linguistics.

关键词： Computing\/Computer Science

来源：评论

学校读者我要写书评

暂无评论

Ontology-based interpretation of natural language

引用

丛书名： synthesis lectures on human language technologies #24.

2014年

作者： Cimiano, Philipp McCrae, John Unger, Andrea Christina

ISBN: (数字)9781608459902

ISBN: (纸本)9781608459902;160845990X

For humans, understanding a natural language sentence or discourse is so effortless that we hardly ever think about it. For machines, however, the task of interpreting natural language, especially grasping meaning beyond the literal content, has proven extremely difficult and requires a large amount of background knowledge. This book focuses on the interpretation of natural language with respect to specific domain knowledge captured in ontologies. The main contribution is an approach that puts ontologies at the center of the interpretation process. This means that ontologies not only provide a formalization of domain knowledge necessary for interpretation but also support and guide the construction of meaning representations. We start with an introduction to ontologies and demonstrate how linguistic information can be attached to them by means of the ontology lexicon model lemon. These lexica then serve as basis for the automatic generation of grammars, which we use to compositionally construct meaning representations that conform with the vocabulary of an underlying ontology. As a result, the level of representational granularity is not driven by language but by the semantic distinctions made in the underlying ontology and thus by distinctions that are relevant in the context of a particular domain. We highlight some of the challenges involved in the construction of ontology-based meaning representations, and show how ontologies can be exploited for ambiguity resolution and the interpretation of temporal expressions. Finally, we present a question answering system that combines all tools and techniques introduced throughout the book in a real-world application, and sketch how the presented approach can scale to larger, multi-domain scenarios in the context of the Semantic Web.

关键词： synthesis lectures human language natural based interpretation ontology

来源：评论

学校读者我要写书评

暂无评论

Learning to Rank for Information Retrieval and Natural language Processing: Second Edition

引用

丛书名： synthesis lectures on human language technologies

2014年

作者： Li, Hang

ISBN: (数字)9781627055857

ISBN: (纸本)9781627055840

Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting based, and Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, colla

关键词：

来源：评论

学校读者我要写书评

暂无评论

Automated Grammatical Error Detection for language Learners: Second Edition

引用

丛书名： synthesis lectures on human language technologies

2014年

作者： Leacock, Claudia Chodorow, Martin Gamon, Michael

ISBN: (数字)9781627050142

ISBN: (纸本)9781627050135

It has been estimated that over a billion people are using or learning English as a second or foreign language, and the numbers are growing not only for English but for other languages as well. These language learners provide a burgeoning market for tools that help identify and correct learners' writing errors. Unfortunately, the errors targeted by typical commercial proofreading tools do not include those aspects of a second language that are hardest to learn. This volume describes the types of constructions English language learners find most difficult: constructions containing prepositions, articles, and collocations. It provides an overview of the automated approaches that have been developed to identify and correct these and other classes of learner errors in a number of languages. Error annotation and system evaluation are particularly important topics in grammatical error detection because there are no commonly accepted standards. Chapters in the book describe the options available to researchers, recommend best practices for reporting results, and present annotation and evaluation schemes. The final chapters explore recent innovative work that opens new directions for research. It is the authors' hope that this volume will continue to contribute to the growing interest in grammatical error detection by encouraging researchers to take a closer look at the field and its many challenging problems.

关键词： Natural language \u0026 Machine Translation

来源：评论

学校读者我要写书评

暂无评论

Computational Modeling of Narrative

引用

丛书名： synthesis lectures on human language technologies

2013年

作者： Inderjeet Mani

ISBN: (纸本)9781608459810

The field of narrative (or story) understanding and generation is one of the oldest in natural language processing (NLP) and artificial intelligence (AI), which is hardly surprising, since storytelling is such a fundamental and familiar intellectual and social activity. In recent years, the demands of interactive entertainment and interest in the creation of engaging narratives with life-like characters have provided a fresh impetus to this field. This book provides an overview of the principal problems, approaches, and challenges faced today in modeling the narrative structure of stories. The book introduces classical narratological concepts from literary theory and their mapping to computational approaches. It demonstrates how research in AI and NLP has modeled character goals, causality, and time using formalisms from planning, case-based reasoning, and temporal reasoning, and discusses fundamental limitations in such approaches. It proposes new representations for embedded narratives and fictional entities, for assessing the pace of a narrative, and offers an empirical theory of audience response. These notions are incorporated into an annotation scheme called Narrative ML. The book identifies key issues that need to be addressed, including annotation methods for long literary narratives, the representation of modality and habituality, and characterizing the goals of narrators. It also suggests a future characterized by advanced text mining of narrative structure from large-scale corpora and the development of a variety of useful authoring aids. This is the first book to provide a systematic foundation that integrates together narratology, AI, and computational linguistics. It can serve as a narratology primer for computer scientists and an elucidation of computational narratology for literary theorists. It is written in a highly accessible manner and is intended for use by a broad scientific audience that includes linguists (computational and formal semanticist

关键词：

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共11页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：