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An Approach to Automated Thesaurus Construction Using Clusterization-Based Dictionary Analysis

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An Approach to Automated Thesaurus Construction Using Clusterization-Based Dictionary Analysis _______________________________________________________PROCEEDING OF THE 17TH CONFERENCE OF FRUCT ASSOCIATION An Approach to Automated Thesaurus Construction Using Clusterization-Based Dictionary Analysis Nadezhda Lagutina†, Ilya Paramonov†, Inna Vorontsova∗, Natalia Kasatkina† †P.G. Demidov Yaroslavl State University, Yaroslavl, Russia ∗Yaroslavl State Pedagogical University named after K.D. Ushinsky, Yaroslavl, Russia [email protected], [email protected], [email protected], [email protected] Abstract—In the paper an automated approach for construc- The paper is structured as follows. Section II contains tion of the terminological thesaurus for a specific domain is a short introduction to the general principles of thesaurus proposed. It uses an explanatory dictionary as the initial text creation and reveals motivation of our research. Section III corpus and a controlled vocabulary related to the target lexicon overviews the papers related to automation of thesaurus cre- to initiate extraction of the terms for the thesaurus. Subdivision of ation. Section IV states the problem under consideration. The the terms into semantic clusters is based on the CLOPE clustering proposed approach is presented in Section V. The results of its algorithm. The approach diminishes the cost of the thesaurus creation by involving the expert only once during the whole application to construction of a terminological thesaurus for the construction process, and only for analysis of a small subset of cardiological lexicon are contained in Section VI. Conclusion the initial dictionary. To validate the performance of the proposed summarizes main achievements of the paper. approach the authors successfully constructed a thesaurus in the cardiology domain. II. GENERAL PRINCIPLES OF THESAURUS CREATION A. Thesaurus definition and purpose I. INTRODUCTION Thesaurus is a polysemantic term treated differently in Thesaurus belongs to the most relevant tools for vocabulary philosophy, lexicography, information retrieval theory etc. In control that applied linguistics and lexicography avail of. A this paper we consider thesaurus as “a vocabulary of controlled terminological thesaurus reflects conceptual relations between indexing language, formally organized so that a priori relation- terminological units and can be referred to as a model of ships between concepts are made explicit” [1]. the given domain. It can be used in systematic organization Such a thesaurus operates special lexical units—terms— of scientific definitions and terms to show how they are that can be used for search (often for automated search) of related to one another as well as other terms belonging to documentary data. Each unit is matched with synonyms or the adjacent scientific areas. Thesaurus is irreplaceable for the correlated words standing in the semantic relations of broader efficient localization and definition of new terms, comparison and narrower terms, part and whole, means and objective etc. and matching of these terms to their equivalents in the termi- The existing variety of semantic relations is usually classified nological systems of other languages [1]. into genus/species and associative. Besides, a thesaurus may The process of specialized thesaurus construction is labor- take a topic-based approach bringing together concepts of a intensive and expensive as it requires processing of big specific domain. amounts of text data and assessment of intermediate and final The two main purposes of such a thesaurus include index- results by an expert [2]. In this regard, automation of thesaurus ing of documents using concepts from semantic resources and construction based on the use of information technologies enhancement of results of the user’s search request using hi- seems to be reasonable. erarchical, associative, and synonymic relations. Additionally, the semantic relations between the words in the thesaurus can In this paper we propose an approach for automated be used to classify and divide documents into clusters. construction of a terminological thesaurus based on semi- automatic analysis of terminological dictionary corpora con- sidered as arranged texts containing a set of terms and def- B. Thesaurus construction procedure initions that demonstrate semantic relations of hierarchical Thesaurus construction is based on creation of the domain (genus/species) and non-hierarchical (synonymic, associative, model. The initial data for the modeling constitutes in a text etc.) types that can be used for divisions of these terms into corpus representative for the domain (dictionaries, textbooks, semantic clusters. reference books, standards etc.). An expert constructing the thesaurus manually analyzes the corpus, makes a list of pre- As a reference case for thesaurus construction using the ferred index terms, and adds these terms to the thesaurus as proposed approach we involve the cardiological lexicon. The keywords [3]. After that, he/she groups the terms into clusters choice of this area is determined by professional demand and defines hierarchical and associative relations between for the lexicographic resources of the kind since they are them. highly desirable for many categories of professionals including general practitioners, scientists, medical translators, medical The macro-composition of the thesaurus is made up by a students etc. classification plan and a set of semantic clusters, e.g., “Heart ISSN 2305-7254 _______________________________________________________PROCEEDING OF THE 17TH CONFERENCE OF FRUCT ASSOCIATION anatomy (norm and pathology)”, “Heart physiology (norm and The authors of [10] propose an automated approach for pathology)”, “Cardiac diseases (functional and organic)” etc. construction of the bilingual thesaurus based on analysis of Japanese and US patents. The hypernym-hyponym relations The minimal unit of the thesaurus structure is an entry are extracted using the patterns (e.g., “A such as B”). Relations containing a detailed description of each term that belongs to between the terms are established with the use of combination a given cluster. The entry provides a user with information on of machine translation and citation analysis methods. grammatical categories of the term, data about grammatical and lexical collocability of the term presented in the form of Review of existing approaches to solve the problem of patterns and illustrative examples. The entry of a thesaurus automation of thesaurus construction allows to identify the traditionally includes terms that stand in relations of semantic used methods and algorithms. It is worth mentioning that most equivalence with the headword (synonyms and opposite terms) of efforts in the existing works are concentrated on initial and related terms [4]. extraction of the terms and definition of relations between the terms, whereas automation of term clustering is studied in- The main disadvantages of manual thesaurus-making are sufficiently. Meanwhile, variety of existing clustering methods high cost, long duration, dependence of the result on expert’s makes research in this area promising. qualification, and restrictions of manual analysis of the large text corpus. Therefore approaches that automate the whole process or its stages are topical in modern linguistics. IV. PROBLEM STATEMENT As has been mentioned, in this paper we propose a solution III. RELATED WORK for the problem of automated construction of the thesaurus for Computer-based lexicography has witnessed numerous at- a specific domain. tempts of automated thesaurus construction [5]. At the mo- As the initial data we use a monolingual explanatory ment, it looks impossible to avoid participation of the expert dictionary in a specific domain. It is important to mention that in the process of thesaurus construction, however there are the explanatory dictionary can cover a broader domain than the many works aimed at partial automation of either the whole target one (e.g., for construction of the thesaurus for cardiology process or its individual stages. area a general medical dictionary would be appropriate). To Most of the related papers consider thesaurus construction start extraction of the related terms we also require a controlled as a process containing several stages including extraction vocabulary of 10–15 terms from the target domain provided of a set of terms from the text corpus, distribution of these by an expert. terms into clusters, and definition of the hypernym-hyponym The automation of thesaurus construction is aimed at the relations between the terms. following operations: For example, in [6] a semi-automatic construction of Jew- ish cross-period thesaurus is described. The authors propose 1) Extraction of candidate terms for the thesaurus from an automated approach to extraction and grouping of terms the initial dictionary; into clusters based on absolute frequency of terms. In this 2) Distribution of the thesaurus terms into semantic process an expert is involved only for manual examination of clusters. the resulted set and removal of irrelevant terms. The other necessary operations are made by the expert. It should be mentioned that the idea of using frequency as The resulted thesaurus should have the following charac- a main characteristic for term extraction is typical for most of teristics: papers. It is applied in many variations, e.g., in [7] the authors use the modified TD-IDF algorithm for that purpose. 1) The set of all terms included in the thesaurus should The similar approach is described in [8] that is devoted to be related
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