Item Type |
Article |
ID |
|
Preview |
Image |
|
Caption |
|
|
Full text |
AN00003152-00000058-0049.pdf
Type |
:application/pdf |
Download
|
Size |
:1.9 MB
|
Last updated |
:May 18, 2009 |
Downloads |
: 1405 |
Total downloads since May 18, 2009 : 1405
|
|
Release Date |
|
Title |
Title |
引用箇所間の意味的な近さに基づく共引用の多値化 : 列挙形式の引用を例として
|
Kana |
インヨウ カショカン ノ イミテキ ナ チカサニ モトヅク キョウインヨウ ノ タチカ : レッキョ ケイシキ ノ インヨウ オ レイ トシテ
|
Romanization |
inyo kashokan no imiteki na chikasani motozuku kyoinyo no tachika : rekkyo keishiki no inyo o rei toshite
|
|
Other Title |
Title |
Multivalued Co-Citation Measure Based on Semantic Distance between Co-Cited Papers in a Citing Paper. A Case Study Focused on Enumeration of Citations
|
Kana |
|
Romanization |
|
|
Creator |
Name |
江藤, 正己
|
Kana |
エトウ, マサキ
|
Romanization |
Eto, Masaki
|
Affiliation |
慶應義塾大学大学院文学研究科
|
Affiliation (Translated) |
Graduate School of Library and Information Science, Keio University
|
Role |
|
Link |
|
|
Edition |
|
Place |
|
Publisher |
Name |
三田図書館・情報学会
|
Kana |
ミタ トショカン ジョウホウ ガッカイ
|
Romanization |
Mita toshokan joho gakkai
|
|
Date |
Issued (from:yyyy) |
2007
|
Issued (to:yyyy) |
|
Created (yyyy-mm-dd) |
|
Updated (yyyy-mm-dd) |
|
Captured (yyyy-mm-dd) |
|
|
Physical description |
|
Source Title |
Name |
Library and information science
|
Name (Translated) |
|
Volume |
|
Issue |
58
|
Year |
2007
|
Month |
|
Start page |
49
|
End page |
67
|
|
ISSN |
|
ISBN |
|
DOI |
|
URI |
|
JaLCDOI |
|
NII Article ID |
|
Ichushi ID |
|
Other ID |
|
Doctoral dissertation |
Dissertation Number |
|
Date of granted |
|
Degree name |
|
Degree grantor |
|
|
Abstract |
Purpose: One typical document retrieval method is to use co-citation. The method is based on the premise that the degree of similarity among co-cited papers is equal in a particular paper. The degree is calculated with binary values: “co-cited” or “not co-cited”. To improve upon this method, the author proposes a multivalued co-citation measure based on semantic distance between co-cited papers.
Methods: To determine the distance between citations, the author measured two machine parseable relationships (location and citing words) between places where papers are cited. In order to evaluate the proposed method, we identified two categories of co-citation: a group with strong relationships indicating “enumerated co-citation” (papers cited within one statement) and a group with weak relationships showing “non enumerated co-citation”. Similarities within each group were calculated and compared using the CiteSeer dataset and 6 major similarity indicators.
Results: All of the similarity indicators showed that the degree of “enumerated co-citation” is higher than “non enumerated co-citation”. Consequently, it became clear that the proposed co-citation measure can be used to distinguish the strength of co-citation more precisely and that it can be applied to large-scale document collections.
|
|
Table of contents |
|
Keyword |
|
NDC |
|
Note |
|
Language |
|
Type of resource |
|
Genre |
|
Text version |
|
Related DOI |
|
Access conditions |
|
Last modified date |
|
Creation date |
|
Registerd by |
|
History |
|
Index |
|
Related to |
|