Optimized Term Extraction Method Based on Computing Merged Partial C-Values

2020 ◽  
pp. 24-49
Author(s):  
Victoria Kosa ◽  
David Chaves-Fraga ◽  
Hennadii Dobrovolskyi ◽  
Vadim Ermolayev
Keyword(s):  
Extraction Method ◽  
Term Extraction

Automatic term recognition based on statistics of compound nouns

Terminology ◽  
2000 ◽  
Vol 6 (2) ◽  
pp. 195-210 ◽  
Author(s):  
Hiroshi Nakagawa
Keyword(s):  
Experimental Evaluation ◽  
Extraction Method ◽  
Recognition Task ◽  
Experimental Results ◽  
Test Collection ◽  
Term Extraction ◽  
Academic Conference ◽  
Compound Nouns ◽  
Automatic Term Recognition ◽  
Technical Terms

The NTCIR1 TMREC group called for participation of the term recognition task which is a part of NTCIR1 held in 1999. As an activity of TMREC, they have provided us with the test collection of the term recognition task. The goal of this task is to automatically recognize and extract terms from the text corpus which consists of 1,870 abstracts gathered from the NACSIS Academic Conference Database. This article describes the term extraction method we have proposed to extract terms consisting of simple and compound nouns and the experimental evaluation of the proposed method with this NTCIR TMREC test collection. The basic idea of scoring a simple noun N of our term extraction method is to count how many nouns are conjoined with N to make compound nouns. Then we extend this score to measure the score of compound nouns because most of technical terms are compound nouns. Our method has a parameter to tune the degree of preference either for longer compound nouns or for shorter compound nouns. As for term candidates, in addition to noun sequences, we may add variations such as patterns of "A no B" that roughly means "B of A" or "A’ś B" and/or "A na B" where "A na" is an adjective. Experimental results of our method are promising, namely recall of 0.83, precision of 0.46 and F-value of 0.59 for exactly matched extracted terms when we take into account top scoring 16,000 extracted terms.

scholarly journals Task Trail Based Enhanced User Experience in Customer Facing Website using Automatic Facet Construction Techniques.

2019 ◽  
Vol 8 (9S3) ◽  
pp. 1057-1060
Keyword(s):  
Extraction Method ◽  
World Wide ◽  
User Behavior ◽  
Extraction Techniques ◽  
End User ◽  
Standard Specification ◽  
Term Extraction ◽  
Construction Techniques ◽  
Novel Method ◽  
Product Standard

World Wide Web is the indispensable source for millions of millions user. The primary goal of the www is provide the most relevant, valid and right information for the end user to who is looking for the information. In this paper we conducted study on various term extraction method used recently by the researchers and we have made a comparative study of various term extraction techniques used in past. Finally we proposed a novel method of improving end user search experience by combining the task trail based user behavior and Automatic facet searching. Also this approach can be further taken forward by enhancing the facets search by referencing the well done Wikipedia for the descriptive based user search goal. The scope of the Automatic facets searching can be further enhanced for the product based product standard specification. Our scopes of work will predominately combining the Automatic facets with the user behavior from the task trail and adding product based standardization to improve the end search experience.

scholarly journals Task Trail Based Enhanced User Experience in Customer Facing Website using Automatic Facet Construction Techniques

2019 ◽  
Vol 8 (9S3) ◽  
pp. 822-825
Keyword(s):  
Extraction Method ◽  
World Wide ◽  
User Behavior ◽  
Extraction Techniques ◽  
End User ◽  
Standard Specification ◽  
Term Extraction ◽  
Construction Techniques ◽  
Novel Method ◽  
Product Standard

World Wide Web is the indispensable source for millions of millions user. The primary goal of the www is provide the most relevant, valid and right information for the end user to who is looking for the information. In this paper we conducted study on various term extraction method used recently by the researchers and we have made a comparative study of various term extraction techniques used in past. Finally we proposed a novel method of improving end user search experience by combining the task trail based user behavior and Automatic facet searching. Also this approach can be further taken forward by enhancing the facets search by referencing the well done Wikipedia for the descriptive based user search goal. The scope of the Automatic facets searching can be further enhanced for the product based product standard specification. Our scopes of work will predominately combining the Automatic facets with the user behavior from the task trail and adding product based standardization to improve the end search experience.

Japanese term extraction using dictionary hierarchy and machine translation system

Terminology ◽  
2000 ◽  
Vol 6 (2) ◽  
pp. 287-311 ◽  
Author(s):  
Jong-Hoon Oh ◽  
Juho Lee ◽  
Kyung-Soon Lee ◽  
Key-Sun Choi
Keyword(s):  
Foreign Language ◽  
Machine Translation ◽  
Extraction Method ◽  
Foreign Languages ◽  
Translation System ◽  
Term Extraction ◽  
Machine Translation System ◽  
Automatic Term Extraction ◽  
Automatic Term Recognition

There have been many studies of automatic term recognition (ATR) and they have achieved good results. However, they focus on a mono-lingual term extraction method. Therefore, it is difficult to extract terms from documents in foreign languages. This article describes an automatic term extraction method from documents in foreign languages using a machine translation system. In our method, we translate documents in foreign languages into documents in Korean and extract terms in the translated Korean documents. Finally the terms recognized from the Korean documents are translated into terms in the foreign language. By using our method, one can extract terms for languages, which one does not know.

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