English Semantics

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  • Semantics is the study of the “toolkit” for meaning: knowledge encoded in the vocabulary of the language and in its patterns for building more elaborate meanings, up to the level of sentence meanings. Pragmatics is concerned with the use of these tools in meaningful communication. Pragmatics is about the interaction of semantic knowledge with our knowledge of the world, taking into account contexts of use. The following is part 2 of the Tài liệu An introduction to English Semantics and Pragmatics, inviting you to refer.

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  • Giáo trình Ngữ nghĩa học tiếng Anh (English Semantics) gồm bốn phần:  Introduction (phần dẫn nhập); Word meaning (nghĩa của từ); Sentence meaning (nghĩa của câu); Utterance meaning (nghĩa của phát ngôn). Mời các bạn cùng tham khảo phần 2 giáo trình sau đây với phần đáp án của các bài tập.

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  •  Giáo trình Ngữ nghĩa học tiếng Anh được biên soạn một cách có hệ thống, dựa trên cơ sở tham khảo có chọn lọc những tư liệu của nước ngoài, kết hợp với kinh nghiệm giảng dạy nhiều năm về môn học này của tác giả và tập thể giảng viên trong bộ môn Ngữ học Anh. Đây là tập giáo trình được biên soạn dùng để giảng dạy môn học Ngữ nghĩa học tiếng Anh (English Semantics) cho sinh viên năm thứ tư Khoa Ngữ văn Anh, Trường Đại học Khoa học Xã hội và Nhân văn, Đại học Quốc gia Thành phố Hồ Chí Minh. Sách gồm 2 phần, sau đây là phần 1 của giáo trình.

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  • This is about how English enables people who know the language to convey meanings. Semantics and pragmatics are the two main branches of the linguistic study of meaning. Both are named in the title of the book and they are going to be introduced here. This book is divided into 2 parts, the following is part 1 of the book. Inviting you to refer.

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  • Tham khảo tài liệu 'assignment on semantics- ngữ nghĩa học', ngoại ngữ, kỹ năng viết tiếng anh phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • Tài liệu tham khảo Journal of semantics

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  • Semantic Web Technologies provides a comprehensive overview of key semantic knowledge technologies and research. The authors explain (semi-)automatic ontology generation and metadata extraction in depth, along with ontology management and mediation. Further chapters examine how Semantic Web technology is being applied in knowledge management (“Semantic Information Access”) and in the next generation of Web services

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  • This is presents a standard and relatively orthodox view of modern linguistic semantics in what we hope is a clear, stimulating, and accessible format. Our emphasis is on getting the student at every stage to think for himself, and so to proceed through the development of concepts in semantics with the confidence and conviction that comes from doing practical exercises with them. Inviting you to refer to part 2 of Tài liệu.

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  • Having lived with the World Wide Web for twenty years, surfing the Web becomes a way of our life that cannot be separated. From latest news, photo sharing, social activities, to research collaborations and even commercial activities and government affairs, almost all kinds of information are available and processible via the Web. While people are appreciating the great invention, the father of the Web, Sir Tim Berners-Lee, has started the plan for the next generation of the Web, the Semantic Web....

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  • This practical coursTài liệu introduces all the basics of semantics in a simple, step-bystep fashion. Each unit includes short sections of explanation with examples, followed by stimulating practice exercises to complete the book. Feedback and comment sections follow each exercise to enable students to monitor their progress. Part 1 presents the contents as: Basic ideas in semantics, from reference, to sense, logic. Inviting you to refer.

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  • As semantic technologies prove their value with targeted applications, there are increasing opportunities to consider their application in social contexts for knowledge, learning, and human development. Semantic Web and Knowledge Management has been accepted as a critical enabler aiming to in crease knowledge-related performance by better use of intellectual assets, in addition to which many governments are forced to increasingly deal with knowledge services that form larger parts of the global economy and society.

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  • The problem of service composition is viewed by many as the \holy grail" in Services Computing. There have been many attempts by researchers from various domains to perform research on this highly relevant and timely sub- ject. One of the goals in Semantic Web research has been to provide con- cepts, methods, and tools to cater for automatic composition of services on the Web.

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  • This book explains, collects and reports on the latest research results that aim at narrowing the so-called multimedia "Semantic Gap": the large disparity between descriptions of multimedia content that can be computed automatically, and the richness and subjectivity of semantics in user queries and human interpretations of audiovisual media. Addressing the grand challenge posed by the "Semantic Gap" requires a multi-disciplinary approach (computer science, computer vision and signal processing, cognitive science, web science, etc....

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  • This paper presents a detailed study of the integration of knowledge from both dependency parses and hierarchical word ontologies into a maximum-entropy-based tagging model that simultaneously labels words with both syntax and semantics. Our findings show that information from both these sources can lead to strong improvements in overall system accuracy: dependency knowledge improved performance over all classes of word, and knowledge of the position of a word in an ontological hierarchy increased accuracy for words not seen in the training data. ...

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  • A number of studies have presented machine-learning approaches to semantic role labeling with availability of corpora such as FrameNet and PropBank. These corpora define the semantic roles of predicates for each frame independently. Thus, it is crucial for the machine-learning approach to generalize semantic roles across different frames, and to increase the size of training instances.

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  • Mapping and classification of chemical compound names are important aspects of the tasks of BioNLP. This paper introduces the architecture of a system for the syntactic and semantic analysis of such names. Our system aims at yielding both the denoted chemical structure and a classification of a given name. We employ a novel approach to the task which promises an elegant and efficient way of solving the problem. The proposed system differs significantly from existing systems, in that it is also able to deal with underspecifying names and class names. ...

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  • This paper presents an open-domain textual Question-Answering system that uses several feedback loops to enhance its performance. These feedback loops combine in a new way statistical results with syntactic, semantic or pragmatic information derived from texts and lexical databases. The paper presents the contribution of each feedback loop to the overall performance of 76% human-assessed precise answers.

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  • This paper reports the results of a preliminary experiment on the detection of semantic variants of terms in a French technical document. The general goal of our work is to help the structuration of terminologies. Two kinds of semantic variants can be found in traditional terminologies : strict synonymy links and fuzzier relations like see-also. We have designed three rules which exploit general dictionary information to infer synonymy relations between complex candidate terms. The results have been examined by a human terminologist.

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  • To verify hardware designs by model checking, circuit specifications are commonly expressed in the temporal logic CTL. Automatic conversion of English to CTL requires the definition of an appropriately restricted subset of English. We show how the limited semantic expressibility of CTL can be exploited to derive a hierarchy of subsets. Our strategy avoids potential difficulties with approaches that take existing computational semantic analyses of English as their starting point--such as the need to ensure that all sentences in the subset possess a CTL translation. ...

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  • We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently. Combining the constraints across many adjectives, a clustering algorithm separates the adjectives into groups of different orientations, and finally, adjectives are labeled positive or negative. ...

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