Concise Wording in Computer Science Research II

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Even if you are an experienced writer, writing an academic paper has unique challenges. The ideas are often complex and highly abstract. In addition, competition for spaces in the top venues is tough, and peer reviewers are distracted and pressed for time. It is not enough to have completed a significant study; if the paper is not readable, few will make the effort to understand the ideas it contains, and it will be rejected.

Concise language has two advantages. First, it conveys those complex ideas as clearly as possible. Second, it reduces your word count. Many journal and conference papers have strict page limits; if you can cut out unnecessary words, there will be more room for your research.

For instance:

It is important to note that each pig has access to water.

Note that each pig has access to water.

Each pig has access to water.

It may seem harsh to get rid of something like “it is important to note,” but every sentence you write in a paper already should be important to note. If it isn’t, it should be deleted.

It is clear from Figure 2 that the second method has a higher performance than the first method.

Clearly, Figure 2 shows that the second method has a higher performance than the first method.

Figure 2 shows that the second method has a higher performance than the first method.

If it really is clear, shouldn’t be necessary to point out that it is clear.

Figure 1 shows the image before automatic segmentation, and Figure 2 shows the image after automatic segmentation.

Figures 1 and 2 show the image before and after automatic segmentation, respectively.

The use of “respectively” has been derided in some circles, but it is still accepted in scientific writing and there are cases where it significantly shortens the text.

More simple examples of how reduce words follow (you can find more examples here):

The largest extreme value point of the distance was 5 m.

The longest distance was 5 m.

 ***

The method was improved through the use of a Hough transform.

The method was improved with a Hough transform.

  ***

All slopes of the regression were positive.

All regression slopes were positive.

  ***

The purpose of Barnum’s approach is to maximize the cohesion in the model.

Barnum‘s approach maximizes the cohesion in the model.

Barnum maximizes the cohesion in the model.

Barnum maximizes the model cohesion.

 ***

Figure 2 shows that the second method has a higher performance than the first method.

Figure 2 shows that the second method performs better than the first.

 ***

The red legos, the green legos, and the blue legos were on the floor, but the other legos were on the table.

The red legos, green legos, and blue legos were on the floor, but the other legos were on the table.

The red, green, and blue legos were on the floor, but the other legos were on the table.

The red, green, and blue legos were on the floor, but the others were on the table.

 ***

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