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Table 1 The 54 topics and their detailed temporal frequency

From: Topic discovery and future trend forecasting for texts

Regress_logist

2

2

10

11

8

11

12

8

5

Random_walk

0

0

4

4

4

10

9

11

19

Time_seri

45

13

10

38

29

29

36

42

37

Neural_network

14

4

2

2

2

5

7

12

7

Social_network

1

6

6

15

19

32

41

62

72

Compon_princip

2

3

9

5

12

8

11

7

9

Mixtur_model

5

8

17

19

14

22

22

6

12

Detect_anomali

3

9

4

13

6

3

15

26

10

Search_engin

6

1

3

8

9

9

15

18

12

Model_graphic

0

1

11

6

10

14

7

17

7

Itemset_frequent

12

14

28

30

21

16

17

15

13

Transfer_learn

0

0

0

0

1

6

10

19

18

Bay_naiv

7

6

17

26

6

4

9

7

4

Year_recent

4

3

4

4

13

8

9

13

11

Model_probabilist

4

7

18

18

26

22

14

15

33

Neighbor_nearest

3

9

5

4

8

13

6

8

7

Analysi_princip

1

1

7

3

10

7

9

7

8

Page_web

21

8

4

9

2

6

7

16

11

Learn_semi-supervis

1

3

7

11

14

20

22

24

30

Squar_least

0

0

4

3

4

7

13

12

10

Collabor_filter

0

3

10

9

2

8

10

16

20

Model_latent

0

1

3

14

13

15

16

19

24

Graph_edg

1

0

8

6

3

4

5

10

22

Detect_outlier

5

2

10

10

25

8

9

12

19

Process_gaussian

3

0

5

13

2

14

13

23

15

Special_case

1

3

6

8

7

10

6

8

8

Select_featur

18

9

28

35

17

32

47

35

77

Model_markov

5

5

19

20

13

10

19

16

19

Field_random

0

0

16

10

8

16

5

18

17

Inform_retriev

11

4

8

10

10

11

12

17

6

Subgraph_graph

1

4

10

0

7

6

8

4

13

Cluster_spectral

0

0

8

6

7

13

9

9

17

Prefer_user

8

3

3

5

4

6

5

10

10

Scale_larg

4

0

4

11

8

15

18

21

26

Learn_activ

6

3

10

8

15

20

29

28

26

Learn_reinforc

2

0

9

5

9

7

9

7

6

Gene_express

5

13

14

9

12

2

9

5

5

Topic_model

4

0

5

0

22

27

22

56

36

System_recommend

4

4

4

10

8

13

8

10

21

Dimension_high

11

11

15

17

18

7

20

14

26

Use_wide

3

4

8

10

11

7

11

9

18

Pattern_sequenti

12

2

5

15

5

10

13

2

8

Loss_function

1

3

7

7

5

6

18

14

7

Model_gaussian

4

2

4

7

11

10

11

11

8

Model_infer

0

0

9

11

11

9

22

31

21

Optim_convex

0

0

2

3

11

8

5

15

9

Global_local

3

1

7

8

6

2

13

15

14

Associ_rule

42

48

14

21

25

4

20

9

5

Text_categor

9

0

9

2

6

10

8

4

10

Model_build

3

1

5

9

5

7

8

12

8

Tree_decis

12

25

37

12

19

11

11

9

22

Dimension_reduct

5

3

6

10

26

19

15

5

22

Machin_support_vector_svm

5

7

12

4

8

9

9

6

7

Pattern_mine_frequent

6

5

10

9

13

10

8

4

12

  1. Each row denotes one topic. The first column denotes the topic, and the 2nd to the 10th columns record the frequency of the topics occurring in the papers published in year 2002, 2003, ... , 2010, respectively