This paper presents a system to support writing a survey of a specific domain. The system utilizes reference information that consists of reference relationships between papers and the information derived from the description around citations. We think the following are inevitable for writing a survey : collecting papers of the specific domain, and understanding their essence and differences among them. Therefore, we firstly extract fragments of papers where the author describes the essence of a referred paper and the differences between his paper and it(we call them reference areas). Then with the information of reference areas, we identify the types of reference relationships that indicate the reasons for citations(we call them reference types). These types make it possible to collect papers in the same domain. The system can display the collection of the papers. It can also show abstracts and reference areas of the collected papers. With the system, we can understand the relationsh...

Following the growing interest in "corpus-based" approaches to computational linguistics, a number of studies have recently appeared on the topic of automatic term recognition or extraction. Because a successful term recognition method has to be based on proper insights into the nature of terms, studies of automatic term recognition not only contribute to the applications of computational linguistics but also to the theoretical foundation of terminology. Many studies on automatic term recognition treat interesting aspects of terms, but most of them are not well founded and described. This paper tries to give an overview of the principles and methods of automatic term recognition. For that purpose, two major trends are examined, i.e. studies in automatic recognition of significant elements for indexing mainly carried out in information retrieval circles, and current research in automatic term recognition in the field of computational linguistics. Keywords Automatic term recognition, au...

This paper describes an experiment that attempts to compare a range of existing collocation extraction techniques as well as the implementation of a new technique based on tests for lexical substitutability. After a description of the experiment details, the techniques are discussed with particular emphasis on any adaptations that are required in order to evaluate it in the way proposed. This is followed by a discussion on the relative strengths and weaknesses of the techniques with reference to the results obtained. Since there is no general agreement on the exact nature of collocation, evaluating techniques with reference to any single standard is somewhat controversial. Departing from this point, part of the concluding discussion includes initial proposals for a common framework for evaluation of collocation extraction techniques.

We introduce the possibility of combining lexical association measures and present empirical results of several methods employed in automatic collocation extraction. First, we present a comprehensive summary overview of association measures and their performance on manually annotated data evaluated by precision--recall graphs and mean average precision. Second, we describe several classification methods for combining association measures, followed by their evaluation and comparison with individual measures. Finally, we propose a feature selection algorithm significantly reducing the number of combined measures with only a small performance degradation. 1

Abstract. The paper presents a method of automatic enrichment of a very large dictionary of word combinations. The method is based on results of automatic syntactic analysis (parsing) of sentences. The dependency formalism is used for representation of syntactic trees that allows for easier treatment of information about syntactic compatibility. Evaluation of the method is presented for the Spanish language based on comparison of the automatically generated results with manually marked word combinations. Key words: collocations, parsing, dependency grammar, Spanish. 1

This chapter has three objectives. First, it argues in favor of more rigorous definitions of the term phraseologism on the basis of six dimensions and exemplifies them for several different kinds of phraseologisms. Second, it reviews the ways in which phraseologisms as defined here have figured in three different linguistic approaches, generative linguistics, cognitive linguistics, and corpus linguistics. Finally, it discusses a few shortcomings in the identification of phraseologisms and points to relevant work to overcome these shortcomings. Key words

This paper describes an experiment that attempts to compare a range of existing collocation extraction techniques as well as the implementation of a new technique based on tests for lexical substitutability. After a description of the experiment details, the techniques are discussed with particular emphasis on any adaptations that are required in order to evaluate it in the way proposed. This is followed by a discussion on the relative strengths and weaknesses of the techniques with reference to the results obtained. Since there is no general agreement on the exact nature of collocation, evaluating techniques with reference to any single standard is somewhat controversial. Departing from this point, part of the concluding discussion includes initial proposals for a common framework for evaluation of collocation extraction techniques.

[I]t is common now to address theoretical issues through the examination of bodies of naturally occurring language use.

By its very nature, corpus linguistics is a distributional discipline. In fact, it has been argued that corpora as such contain nothing but distributional frequency data, more specifically distributional data of two or three types, depending on how one wants to look at it:

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