├── AUTHOR.txt
├── LICENSE
├── README.md
├── extraction_code.py
└── result.JPG
/AUTHOR.txt:
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1 | +Copyright 2018 UNIST Yeeun Chun under XAI Project supported by Ministry of Science and ICT, Korea
2 | +
3 | +# This is the list of UNIST Yeeun Chun for copyright purposes.
4 | +# This does not necessarily list everyone who has contributed code, since in
5 | +# some cases, their employer may be the copyright holder. To see the full list
6 | +# of contributors, see the revision history in source control
7 |
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/LICENSE:
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/README.md:
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1 | # Annual-Report-Extraction
2 |
3 | ### **Description**
4 | >Extract 'Management's Discussion & Analysis" from annual reports
5 |
6 |
7 | 
8 |
9 |
10 |
11 | ## Reference Code
12 | Based on code by [Noah Smith](http://www.cs.cmu.edu/~ark/10K/data/extract_MDA.pl)
13 |
14 | ## Requirements
15 | + re (2.2.1)
16 |
17 | ## License
18 | [Apache License 2.0](https://github.com/OpenXAIProject/tutorials/blob/master/LICENSE "Apache")
19 |
20 | ## Contacts
21 | If you have any question, please contact Ingeoun(chaneeh@unist.ac.kr).
22 |
23 |
24 |
25 |
26 | # XAI Project
27 |
28 | **This work was supported by Institute for Information & Communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2017-0-01779, A machine learning and statistical inference framework for explainable artificial intelligence)**
29 |
30 | + Project Name : A machine learning and statistical inference framework for explainable artificial intelligence(의사결정 이유를 설명할 수 있는 인간 수준의 학습·추론 프레임워크 개발)
31 |
32 | + Managed by Ministry of Science and ICT/XAIC 
33 |
34 | + Participated Affiliation : UNIST, Korea Univ., Yonsei Univ., KAIST, AItrics
35 |
36 | + Web Site :
37 |
38 |
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/extraction_code.py:
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1 | import re
2 | from collections import defaultdict
3 |
4 | p5 = re.compile("(\S+)", re.MULTILINE|re.I)
5 | def length_in_words(sub_element):
6 | tmp2 = p5.findall(sub_element)
7 | return len(tmp2)
8 |
9 | f = open("756109104-10-K-19960321.txt")
10 | #f = open("test.txt", 'r')
11 | x = ""
12 | for line in f:
13 | x += line
14 |
15 | p1 = re.compile("([^\"])(item\s+7[^0-9a-z\"]*management(?:[^0-9a-z]{0,3}s)?\s+discussions?\s+and\s+analysis\s+of\s+(?:financial\s+conditions?\s+|results\s+of\s+operations?)(?:\s+and\s+results\s+of\s+operations?|\s+and\s+financial\s+conditions?)?)", re.I|re.DOTALL|re.MULTILINE)
16 | p2 = re.compile("([^\"])(item\s+7[^0-9a-z\"]*a[^0-9a-z\"]*(?:quantitative\s+and\s+(?:qualitative|qualification)\s+disclosures?\s+about\s+)?market\s+risk)", re.I|re.DOTALL|re.MULTILINE)
17 | p3 = re.compile("([^\"])(item\s+8[^0-9a-z\"]*.{0,40}financial\s+statements[^\.])", re.I|re.DOTALL|re.MULTILINE)
18 | x = p1.sub("\1#######ITEM7:\2#######", x)
19 | x = p2.sub("\1#######ITEM7A:\2#######", x)
20 | x = p3.sub("\1#######ITEM8:\2#######", x)
21 |
22 | #x = "####### abc ####### abc #########"
23 |
24 | x_list = x.split("#######") # <== we can not use regular exp!!
25 | y_list = []
26 | z_list = []
27 | p4 = re.compile("^(ITEM(?:7|7A|8)):(.*)$", re.MULTILINE)
28 | for i in range(len(x_list)):
29 | tmp = p4.findall(x_list[i])
30 | if(len(tmp) != 0):
31 | z_list.append(tmp[0][1])
32 | y_list.append(str(i) + ':' + tmp[0][0])
33 | else:
34 | z_list.append(x_list[i])
35 | y_list.append(str(i) + ':' + str(length_in_words(x_list[i])))
36 |
37 | #print(y_list)
38 | y = ' '.join(y_list)
39 | #print y
40 | p6 = re.compile("((?:\d+:ITEM7 \d+:\d+ )+(?:\d+:ITEM7A \d+:\d+ )*)(?:\d+:ITEM8 \d+:\d+\s*)+")
41 | M_list = p6.findall(y)
42 |
43 | p7 = re.compile("\d+:")
44 | p8 = re.compile("^\d+$")
45 |
46 |
47 | best = 0
48 | bestseq = ""
49 | for i in range(len(M_list)):
50 | m = M_list[i]
51 | m = p7.sub("", m)
52 | m_list = m.split(" ")
53 | v = 0
54 | for j in range(len(m_list)):
55 | q = m_list[j]
56 | t_list = p8.findall(q)
57 | if (len(t_list) != 0):
58 | v += int(q)
59 | if (v > best):
60 | best = v
61 | bestseq = M_list[i]
62 |
63 | # v, best, bestseq
64 | # 1071 57633 3895:ITEM7 3896:57628 3897:ITEM7 3898:5
65 |
66 | p9 = re.compile(":\S+")
67 | p10 = re.compile("\s*$")
68 | kept = defaultdict(lambda: 0)
69 | if(bestseq != ""):
70 | bestseq = p9.sub("", bestseq)
71 | mm_list = bestseq.split(" ")
72 | print mm_list
73 | for i in range(len(mm_list)):
74 | mm = mm_list[i]
75 | if mm == '':
76 | continue
77 | z_list[int(mm)] = p10.sub("\n", z_list[int(mm)])
78 | print z_list[int(mm)]
79 | kept[int(mm)] = 1
80 | else:
81 | print "no match"
82 |
83 | p11 = re.compile("\b\d+:", re.MULTILINE)
84 | y = p11.sub("", y )
85 | #print y
86 | yy_list = y.split(" ")
87 | print(yy_list)
88 | for i in range(len(yy_list)):
89 | if kept[i] != 0:
90 | print "*"
91 | print yy_list[i]+" "
92 | print "\n"
93 |
94 |
95 |
96 | #print(m_list)
97 |
98 |
99 | #print(x)
100 | #print y
101 | #item_list = p.findall("hello")
102 | #for item in item_list[:]:
103 | # print(item)
104 |
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/result.JPG:
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https://raw.githubusercontent.com/OpenXAIProject/Annual-Report-Extraction/030462034b737ea03c2569f56dd1fab46dc50c99/result.JPG
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