نتایج جستجو برای: based on liebers lexical semantic representation theory lieber
تعداد نتایج: 9509085 فیلتر نتایج به سال:
Pustejovsky, J. and B. Boguraev, Lexical knowledge representation and natural language processing, Artificial Intelligence 63 (1993) 193-223. Traditionally, semantic information in computational lexicons is limited to notions such as selectional restrictions or domain-specific constraints, encoded in a "static" representation. This information is typically used in natural language processing by...
This paper examines a particular PROLOG implementation of Discourse Representation theory (DR theory) constructed at the University of Texas. The implementation also contains a Lexical Functional Grammar parser that provides f-structures; these f-structures are then translated into the semantic representations posited by DR theory, structures which are known as Discourse Representation Structur...
Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new impr...
The purpose of designing the lexical semantic representation model E-HowNet is for natural language understanding. E-HowNet is a frame-based entity-relation model extended from HowNet to define lexical senses and achieving compositional semantics. The followings are major extension features of E-HowNet to achieve the goal. a) Word senses (concepts) are defined by either primitives or any well-d...
We define learning as the generation of meaningful knowledge representations which can be utilized in future decision making. Optimal learning entails that these knowledge representations be integrated with prior knowledge. In this paper, we introduce a knowledge representation based on an integration of a variety of shallow semantic parsing techniques. Entity detection, event detection, semant...
Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...
The article provides an insight into a problem of lexical semantic change. A short historical outline of the development of semantic studies is given. The authors analyze some of the most important stages in the history of the formation of this field. The existing approaches to dealing with form and meaning, namely semasiological and onomasiological ones are discussed. The authors consider the ...
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
In this talk I would like to address some issues of major importance in lexical semantics. In particular, I will discuss four topics relating to current research in the field: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central problems facing the l...
Books describing novel approaches to machine translation (MT) are always welcome. This is all the more so when the approach is one not covered by general MT surveys such as those in Hutchins and Somers (1992) or Arnold et al. (1994). Bonnie Jean Dorr's Machine Translation: A View from the Lexicon is a book with a novel approach. It describes the interlingual MT system UNITRAN rooted in two Mass...
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