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71-80 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：

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Sébastien Harispe Sylvie Ranwez Stefan Janaqi Jacky Montmain

ISBN: (数字)9783031021565

ISBN: (纸本)9783031010286

Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better unders

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Statistical language Models for Information Retrieval 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： ChengXiang Zhai

ISBN: (数字)9783031021305

ISBN: (纸本)9783031010026

As online information grows dramatically, search engines such as Google are playing a more and more important role in our lives. Critical to all search engines is the problem of designing an effective retrieval model that can rank documents accurately for a given query. This has been a central research problem in information retrieval for several decades. In the past ten years, a new generation of retrieval models, often referred to as statistical language models, has been successfully applied to solve many different information retrieval problems. Compared with the traditional models such as the vector space model, these new models have a more sound statistical foundation and can leverage statistical estimation to optimize retrieval parameters. They can also be more easily adapted to model non-traditional and complex retrieval problems. Empirically, they tend to achieve comparable or better performance than a traditional model with less effort on parameter tuning. This book systematically reviews the large body of literature on applying statistical language models to information retrieval with an emphasis on the underlying principles, empirically effective language models, and language models developed for non-traditional retrieval tasks. All the relevant literature has been synthesized to make it easy for a reader to digest the research progress achieved so far and see the frontier of research in this area. The book also offers practitioners an informative introduction to a set of practically useful language models that can effectively solve a variety of retrieval problems. No prior knowledge about information retrieval is required, but some basic knowledge about probability and statistics would be useful for fully digesting all the details. Table of Contents: Introduction / Overview of Information Retrieval Models / Simple Query Likelihood Retrieval Model / Complex Query Likelihood Model / Probabilistic Distance Retrieval Model / language Models for Special Retri

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Computational Modeling of human language Acquisition 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Afra Alishahi

ISBN: (数字)9783031021404

ISBN: (纸本)9783031010125

human language acquisition has been studied for centuries, but using computational modeling for such studies is a relatively recent trend. However, computational approaches to language learning have become increasingly popular, mainly due to advances in developing machine learning techniques, and the availability of vast collections of experimental data on child language learning and child-adult interaction. Many of the existing computational models attempt to study the complex task of learning a language under cognitive plausibility criteria (such as memory and processing limitations that humans face), and to explain the developmental stages observed in children. By simulating the process of child language learning, computational models can show us which linguistic representations are learnable from the input that children have access to, and which mechanisms yield the same patterns of behaviour that children exhibit during this process. In doing so, computational modeling provides insight into the plausible mechanisms involved in human language acquisition, and inspires the development of better language models and techniques. This book provides an overview of the main research questions in the field of human language acquisition. It reviews the most commonly used computational frameworks, methodologies and resources for modeling child language learning, and the evaluation techniques used for assessing these computational models. The book is aimed at cognitive scientists who want to become familiar with the available computational methods for investigating problems related to human language acquisition, as well as computational linguists who are interested in applying their skills to the study of child language acquisition. Different aspects of language learning are discussed in separate chapters, including the acquisition of the individual words, the general regularities which govern word and sentence form, and the associations between form and meaning. For eacho

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Discourse Processing 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Manfred Stede

ISBN: (数字)9783031021442

ISBN: (纸本)9783031010163

Discourse Processing here is framed as marking up a text with structural descriptions on several levels, which can serve to support many language-processing or text-mining tasks. We first explore some ways of assigning structure on the document level: the logical document structure as determined by the layout of the text, its genre-specific content structure, and its breakdown into topical segments. Then the focus moves to phenomena of local coherence. We introduce the problem of coreference and look at methods for building chains of coreferring entities in the text. Next, the notion of coherence relation is introduced as the second important factor of local coherence. We study the role of connectives and other means of signaling such relations in text, and then return to the level of larger textual units, where tree or graph structures can be ascribed by recursively assigning coherence relations. Taken together, these descriptions can inform text summarization, information extraction,discourse-aware sentiment analysis, question answering, and the like. Table of Contents: Introduction / Large Discourse Units and Topics / Coreference Resolution / Small Discourse Units and Coherence Relations / Summary: Text Structure on Multiple Interacting Levels

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Linguistic Structure Prediction 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Noah A. Smith

ISBN: (数字)9783031021435

ISBN: (纸本)9783031010156

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Automated Grammatical Error Detection for language Learners 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Claudia Leacock Martin Chodorow Michael Gamon Joel Tetreault

ISBN: (数字)9783031021374

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 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. Table of Contents: Introduction / History of Automated Grammatical Error Detection / Special Problems of language Learners / language Learner Data / Evaluating Error Detection Systems / Article and Preposition Errors / Collocation Errors / Different Approaches for Different Errors / Annotating Learner Errors / New Directions / Conclusion

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Embeddings in Natural language Processing 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Mohammad Taher Pilehvar Jose Camacho-Collados

ISBN: (数字)9783031021770

ISBN: (纸本)9783031010491

Embeddings have undoubtedly been one of the most influential research areas in Natural language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

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 2

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Hang Li

ISBN: (数字)9783031021558

ISBN: (纸本)9783031010279

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, collabora

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Computational Modeling of Narrative 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Inderjeet Mani

ISBN: (数字)9783031021473

ISBN: (纸本)9783031010194

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 NarrativeML. 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 semanticists

关键词： Artificial Intelligence Natural language Processing (NLP) Computational Linguistics

来源：评论

学校读者我要写书评

暂无评论

Building and Using Comparable Corpora for Multilingual Natural language Processing 1

引用

丛书名： synthesis lectures on human language technologies

1000年

作者： Serge Sharoff Reinhard Rapp Pierre Zweigenbaum

ISBN: (数字)9783031313844

ISBN: (纸本)9783031313837;9783031313868

This book provides a comprehensive overview of methods to build comparable corpora and of their applications, including machine translation, cross-lingual transfer, and various kinds of multilingual natural language processing. The authors begin with a brief history on the topic followed by a comparison to parallel resources and an explanation of why comparable corpora have become more widely used. In particular, they provide the basis for the multilingual capabilities of pre-trained models, such as BERT or GPT. The book then focuses on building comparable corpora, aligning their sentences to create a database of suitable translations, and using these sentence translations to produce dictionaries and term banks. Then, it is explained how comparable corpora can be used to build machine translation engines and to develop a wide variety of multilingual applications.

关键词： Natural language Processing (NLP) Artificial Intelligence Computer Applications Computer Science, general Computational Linguistics Machine Learning

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 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：