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1 19 A Proposal of Text Classification using Formal Concept Analysis

2 ( ) Hasse Web Reuters Concept Explorer 2 4 said i

3 Abstract A Proposal of Text Classification using Formal Concept Analysis Akinori Moriki Formal concept analysis, visualizing relations among objects by partial order relation, is a data analysis method based on lattice theory. The method is used Hasse s diagram which is generated by a 2 dimensional table consisted of objects and attributes. In this thesis, formal concept analysis is applied to articles included in Reuters for obtaining main subjects and summarization of the articles. Objects are the news articles, and attributes are words included in all of the article. Concept lattice is constructed with Concept Explorer, the software for formal concept analysis. In the result, prepositions and articles, such as a, an, and the, are located on high layer of the concept lattice. This situation indicates that prepositions and articles are common words for many news articles. They are, however, not suggestive for news contents, since those words are not meaningful. On the other hand, nouns and verbs are generally meaningful words, and they are suggestive for news contents. Those words are located on low layers of the concept lattice, and are common for 2 to 4 articles. However, said appears on high layer of the concept lattice. This causes by the name of speaker in news. Therefore, nouns and verbs appeared on high layer are indicate tendencies of all articles, and nouns and verbs appeared on low layer indicate relation and association among texts. key words formal concept analysis, text classification, concept lattice ii

4 CSV iii

5 28 iv

6 (conceptlattice) (concept) [5] v

7 CSV vi

8 1 Web Web Web 1981 Darmstadt Rudolf Wille 2 Hasse 2 1

9 [2] Concept Explorer[3] Hasse Hasse

10 Hasse 2.1 Hasse Hasse 2.1 3

11 2.1 a b c d ({2,3}, {c}) ({1,2,3,4}, empty) ({2,4}, {d}) : node(concept) ({1,4}, {b}) ({2}, {c,d}) ({4}, {b,d}) ({1}, {a,b}) (empty, {a,b,c,d}) (concept lattice) 2.1 ({2}, {c,d}) ({4}, {b,d}) ({2}, {c,d}) {2} {c,d} ({4}, {b,d}) {4} {b,d} 2 4

12 2.1 concept Extent A Object Intent B Attribute 2.2 (concept) [5] ({2,3}, {c}) ({2,4}, {d}) 2 {2,3} {c} {2,4} {d} ({2,3}, {c}) ({2}, {c,d}) ({2,4}, {d}) ({2}, {c,d}) ({4}, {b,d}) 2.1 ({2,3}, {c}) ({2}, {c,d}) {2} ({2,3}, {c}) ({3}, {c}) ({2,4}, {d}) {2}{4} {d} ({2}, {c,d}) ({2,3}, {c}) ({2,4}, {d}) {c}{d} {2} 5

13 2.1 Hasse ( 2.2) Hasse ({2,3}, {c}) {2,3} {c} ({Arctic Monkeys,Metallica}, {Rock}) ({James Blunt}, {Pop}) 2 ({Arctic Monkeys,Metallica}, {Rock}) {Rock} ({James Blunt}, {Pop}) {Pop} ({Arctic Monkeys,Metallica}, {Rock}) ({James Blunt}, {Pop}) Rock Pop ({Arctic Monkeys,Metallica}, {Rock}) { } { } {Punk, } { } { } { } Rock ({Slipknot}) {Rock} { } { } 6

14 2.1 Pop Rock Punk Sum 41 Red Hot Chili Peppers Oasis Linkinpark Killswitch Engage Fall Out Boy Slipknot Marilyn Manson Arctic Monkeys Maroon5 Metallica James Blunt 2.2 { } Slipknot Rock ({Sum 41}) {Rock} {Punk, } {Pop} Sum 41 Punk Pop Rock 7

15 CREDO[4] Claudio Carpinet Gianni Romano 2 Web Web Yahoo! CREDO Web Web Yahoo! 8

16 2.2 Google Web Web 9

17 3 3.1 Web Reuter 21578, Distribution 1.0[2] SGML <BODY> </BODY> *.txt txt 10

18 path CSV CSV CSV CSV K K 1 0 K = w 0,0 w 0,attr w obj 1,0 w obj 1,attr 1 (3.1) obj attr ( ) w 11

19 3.3,Showers,continued,throughout,,hotels text 1,1,1,1,,0 text 2,0,0,0,,0 text 3,0,0,0,,0 text 4,0,0,0,,0 text 5,0,0,0,,1 3.1 CSV m g wobj-1,attr-1, CSV CSV Web Concept Explorer version 1.3[3] Concept Explorer Yevtushenko Concept Explorer CSV Concept Explorer 12

20 3.3 text 1 text text N context Concept Explorer CSV Concept Lattice CSV 3. Concept Explorer CSV 4. CSV 5. 13

22 n n n n n 4.2 said 2 Concept Explorer CSV

23 said

24 n n n 4.2 n 1 2 n 17

30 4.1 実験結果と考察図 4.8 テキスト 45 個の概念束図 4.9 テキスト 50 個の概念束 23

31 5 Web [2] 2 4 said 2 4 said said 24

32 Concept Explorer[3] 60 25

35 [1] Bernhard Ganter TU Dresden, Formal Concept Analysis : Methods and Application in Computer Science, 2002 [2] Reuters Text Categorization Collection [3] Yevtushenko, Concept Explorer version [4] C. Carpinet, G. Romano, CREDO [5], vol. 19 no. 2 pp

1 1 tf-idf tf-idf i

14 A Method of Article Retrieval Utilizing Characteristics in Newspaper Articles 1055104 2003 1 31 1 1 tf-idf tf-idf i Abstract A Method of Article Retrieval Utilizing Characteristics in Newspaper Articles