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Dieses Kapitel geht den Strategien nach, um die Wahrscheinlichkeit zu erhöhen, dass eine Forschungsarbeit an hochrangigen akademischen Orten akzeptiert wird. Es beginnt damit, die Bedeutung des Verständnisses der korrekten Positionen von Rezensenten und Autoren zu betonen, wobei hervorgehoben wird, dass Rezensenten oft fleißige Freiwillige sind, die mehrere Arbeiten schnell bewerten müssen. Das Kapitel rät Forschern, die Rezensenten als "Könige und Königinnen" zu behandeln und ihnen zu dienen, indem sie sicherstellen, dass ihre Arbeiten klar, motiviert und technisch einwandfrei sind. Außerdem wird die Notwendigkeit betont, Umfang und Zielgruppe jeder Konferenz oder Zeitschrift vor der Einreichung gründlich zu verstehen, um sicherzustellen, dass der Aufsatz mit ihren Interessen und Standards im Einklang steht. Das Kapitel identifiziert fünf Hauptgründe für die Ablehnung von Papieren: mangelnde Motivation, begrenzte Neuheit / technischer Beitrag, schwache Präsentation, unzureichende verwandte Arbeit und fehlende wichtige Experimente. Es gibt praktische Tipps, wie man diese Fallstricke vermeiden kann, wie etwa relevante Fragen zu stellen, um die Forschung zu motivieren, neue Probleme oder interdisziplinäre Forschungsbereiche zu finden, einen logischen Ablauf in der Präsentation zu gewährleisten, umfassende Literaturbefragungen durchzuführen und Experimente akribisch zu planen. Darüber hinaus wird in diesem Kapitel die Wichtigkeit des ernsthaften Umgangs mit Revisionen, des Dienstes zur Zufriedenheit der Rezensenten und der Einreichung mehrerer Arbeiten diskutiert, um die Chancen auf Akzeptanz zu erhöhen. Abschließend werden die Forscher ermutigt, niemals aufzugeben, und betont, dass Beharrlichkeit und kontinuierliche Unterwerfung letztlich zu Akzeptanz in hochrangigen Einrichtungen führen können.
KI-Generiert
Diese Zusammenfassung des Fachinhalts wurde mit Hilfe von KI generiert.
Abstract
In this chapter, we further discuss the correct mindsets for students in order to further enhance the chance for making a paper accepted in a top-tier venue, which can be summarized into the following six types.
In this chapter, we further discuss the correct mindsets for students in order to further enhance the chance for making a paper accepted in a top-tier venue, which can be summarized into the following six types.
6.1 Understand the Correct Positions of Reviewers and Authors
There are three main points that should be mentioned for the review process.
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1.
Reviewers are normally the professors and researchers, who have their own duties in their universities/research companies/research labs. They can be extremely busy.
2.
Reviewers are volunteers, who are not paid by any organization.
3.
Reviewers normally need to review a lot of papers at the same time. Using ICDE 2024 (second round) as an example, each reviewer needs to review roughly 18 papers (with 12 pages and IEEE double column format) in one and a half month.
Based on the above discussion, we expect that reviewers cannot spend a lot of time for reading each paper and have a right to reject a paper that they are not confident about the quality in a short period of time. Therefore, students should have the mindset that reviewers are the customers (or Kings and Queens) and they should be the ones who serve them. In other words, students should know the correct positions of reviewers and authors (see Fig. 6.1) so that they can change their attitudes for writing research papers.
Fig. 6.1
Wrong and correct positions for reviewers and authors
Each conference/journal has its own policy/scope for accepting papers. Do not submit papers to the venues that do not match together. This figure is obtained from the official webpage of ICDE 2025
Every conference/journal has its own scope and target readers, which are normally listed in its webpage. Students should check carefully about this information in the webpage before they choose to submit a paper in that conference/journal. Using ICDE 2025 as an example (see Fig. 6.2),1 this conference explicitly mentions that it does not accept a paper that purely advances the machine learning model without any data management issues. Therefore, students should not submit anything about this to this conference. Otherwise, the acceptance chance is zero and there will be no meaningful comments from reviewers (i.e., this is a waste of time.). In addition, students should also check those papers from the target conferences/journals and understand the research/writing styles from them. The main reason is that reviewers will normally reject those papers that do not match their styles. For example, if those venues love those papers related to AI/ML, it is hard for them to accept some papers related to system development. Using the first author of this book as an example, he submitted one paper about using the piecewise-linear function to improve the efficiency for training SVM models with additive kernels to the data management venues (SIGMOD, VLDB, and ICDE). Although this paper is still within the scope of these venues, those reviewers were not very keen to this paper and mentioned that this topic is not interesting. Once he submitted this paper to TKDE, in which the research style aligns with that paper, he first got a revision and then got an acceptance.
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6.3 Understand Five Main Reject Reasons by Reviewers
In order to reject a paper by a top-tier conference/journal, reviewers normally need to provide at least one of these five main reasons, which are (1) lack of motivation, (2) limited novelty/technical contribution, (3) weak presentation, (4) insufficient related work, and (5) missing a lot of important experiments. Therefore, once the students think that they are confident for avoiding all these reasons, their papers can have a relatively high chance to be accepted in a top-tier conference/journal. Here, we discuss how to avoid these reject reasons.
Lack of motivation. When the student writes everything, they need to provide a clear motivation. Then, some students may raise this question. How to provide motivation? Our answer is “always ask questions”. Suppose that the student wants to work on one research topic. They need to immediately raise the following questions.
What are the applications for this topic?
Who are the users?
How do the users use this?
What are the challenges for this problem/topic?
(For old topic) There have been some existing research studies. Why do you need to make another solution? (Is it more accurate? Is it more efficient?)
(For new topic) No one has studied this before. Why do you need to be the first to study this topic? (Solid motivation should be provided.)
If the students can clearly answer all the above questions, they can tell a complete story of their work. We can state that their research topics are clearly motivated. If the students cannot provide concrete answers, they need to think deeply about the answers in order to motivate their research topics.
Limited novelty/technical contribution. This comment is somehow the most difficult one for students (even for some faculty members). In order to avoid this comment, students need to read various papers in the target venues in order to understand the technical depth. Here, we provide two strategies for avoiding this comment.
Find new problems/settings. We would like to emphasize that reviewers are normally lenient to those research papers that focus on new research problems (or new settings). The reason is that the paper looks new starting from the early stage (problem/setting). Therefore, we encourage that students should think of a new problem rather than conducting research in an old problem (e.g., similarity search based on Euclidean distance, which has been done three decades ago). In other words, students should not simply follow others. With a new problem/setting, it is also easy for students to think of novel solutions with solid technical contributions due to the lack of competitors.
Find interdisciplinary research problems that are not sufficiently considerable byresearchers in the computer science field. Using the first author of this book as an example, he worked on the research problem of developing efficient algorithms for Kernel Density Visualization (KDV). Although KDV is mainly used in GIS/geography communities, it is also related to spatiotemporal data management in the computer science field. However, there is a lack of researchers in computer science who focus on this problem. As such, there is a big room for him to develop efficient solutions for handling this problem and its variants. In addition, other researchers also do not care about this problem at that time. With these reasons, he can publish many top-tier papers in the data management/data mining venues that are related to this problem.
Weak presentation. When students write papers, they need to have this word in mind, which is “connection”. If a paper is disconnected, it is very hard for readers to understand the flow of the paper. Here, we provide some examples of common mistakes.
Example 1
Some students have provided the problem definition in Section 2 and have mentioned one method in Section 3. However, the proposed method does not have enough linkage with the problem definition. Therefore, this can let readers raise the question for whether this method is really solving the problem.
Example 2
Some students first present the method A and then the method B. However, there is no linkage between these two methods. Therefore, readers can raise the concern for why they need to propose two methods but not the best one.
Example 3
Some students discuss existing methods in the “Preliminaries” section and present their new method without any reason (i.e., loses the linkage between the existing methods and the new method). Therefore, readers may wonder why they need to develop this new method.
In order to avoid the above mistakes, we emphasize that students need to make sure that everything is connected naturally when they are writing research papers. Once the students achieve this goal, they can easily address this comment.
Insufficient related work. Students need to make sure that they can provide a comprehensive survey for their research topics. Using the first author of this book as an example, he classifies the related work into different categories. For each category, he provides excessive references in prestigious conferences/journals (most of them are published recently) and mentions the differences between each category and his method. There are two main advantages for this approach. First, it is very hard for reviewers to figure out some missing references. Second, even though reviewers have identified a missing reference, it can belong to one of the categories, which indicates that this reference still has the same differences compared with his method. As such, it is hard for reviewers to use this reason to reject the paper.
Missing a lot of important experiments. Many (junior) students may not think carefully about which experiments they need to conduct when they prepare for their research papers. As such, they may have missed a lot of important experiments when they reach the deadline of submission. Here, we suggest that they provide the plan for which experiments they need to conduct in the first place. Consider the first author of this book as an example. When he worked on a research topic, he had the plan for conducting which experiments in advance (see Fig. 6.3). Observe that he clearly wrote down which variable he should vary in each experiment. Once this plan is ready, what he needs to do is to write down the script file to vary this variable for testing the performance.
Fig. 6.3
The first author of this book plans for the experiments in advance so that he does not miss some important experiments before the paper submission
If a student is lucky to have a chance for revision, we need to congratulate him/her because it is highly possible that the paper can be accepted in the conference or journal. In the rule of thumb, the acceptance rate is normally more than 80% if a revision is granted for a paper. As an example, the acceptance rate of VLDB 2015 is 84.6% after revision. Therefore, students need to be very serious about the revision. Figure 6.4 shows the correct and wrong approaches for students to deal with the revision.
In a revision, the reviewer can possibly ask some questions for the authors to change the paper (e.g., add additional experiments or change the presentation). Some students may be very annoyed about these comments because they need to spend more time to deal with them (by implementing some methods or thinking of new structures for writing the papers). Therefore, they will tend to pass over these questions by finding some excuses to avoid doing it. Here, we need to emphasize that this mindset is completely wrong. If the reviewer has already provided concrete (and doable) experiments (e.g., ask the students to add the running-time experiment by changing the dataset size), the students need to add it either in the response letter, in the paper, or in the technical report no matter whether this experiment is meaningful or not. They need to know that reviewers are the ones who can determine the acceptance/rejection of a paper. They are Kings and Queens. Therefore, in order to make a paper accepted, all they need to do is to make them happy (satisfied). If they figure out that the authors (i.e., the students) do not have the intension to address their comments, they can feel very angry and give a rejection.
Fig. 6.4
The correct and wrong approaches for handling the comments from reviewers in a revision
Figure 6.5 provides an analogy for dealing with revision. A student needs to act as a servant who serves for a customer (i.e., a reviewer). As a servant, all he/she needs to do is to make the customer happy. Once the customer is happy, the servant can receive some benefits from the customer (e.g., tips). Otherwise, the customer can be angry and writes a complaint letter so that the servant can lose the job.
Fig. 6.5
This is an analogy for dealing with a revision. A productive student (upper one) needs to act as a servant to make a reviewer (i.e., a customer (or a king)) happy, while an unproductive student (lower one) makes a reviewer (i.e., a customer (or a king)) angry
6.5 The More Papers You Submit, the More “Accept” You Get
Many students may wonder how to submit a paper so that they can ensure that the paper must be accepted in the conference/journal. Here, we would like to point out that we can only try our best to improve the research paper. However, we cannot say that there is a 100% chance for a paper to be accepted in a top-tier venue after we submit that paper (even though we have followed all those suggestions in this book). There are two main reasons.
The acceptance rate of top-tier venues is normally low. Many top-tier venues, including SIGMOD, SIGKDD, VLDB, and ICDE, have the acceptance rate of 15–30%. As an example, the acceptance rate of SIGKDD 2025 (February Cycle) is only 18.4% (see Fig. 6.6). Therefore, we need to expect that we can only have one paper accepted in this conference once we have submitted five papers on average.
The authors in top-tier venues are mostly from top universities/research labs. Note that top-tier venues are very competitive. Many researchers in top universities/research labs (e.g., MIT, Stanford, Harvard, Tsinghua, and AT&T lab) also submit papers to these venues. Since these researchers can possibly be the best of the best in the world, this can further increase the difficulties for a paper (of a newbie with a lack of experience) to be accepted in these venues.
Fig. 6.6
The acceptance rate of SIGKDD 2025 (February Cycle) is only 18.4%
Based on the above reasons, some students may observe that their hard work for submitting many papers seems to be useless and may raise this question. Does it mean that they should not work hard for submitting many papers? The answer is no. Here, we would like to use the probability concept to explain this. Suppose that the probability of acceptance for each submission is p. If the student has n papers for submission. Obviously, the expected value of acceptance is \(n\times p\), based on the concept of Binomial distribution. Therefore, if the number of submissions n is larger, the number of acceptances must also be larger (given that p is not zero). Here, we consider the first author of this book as an example (see Fig. 6.7). In 2024, he had submitted seven papers to the VLDB conference (with the acceptance rate of roughly 20%). Note that only two papers are accepted in this conference. As such, the number of accepted papers is just slightly higher than the expected number (\(7\times 0.2=1.4\)). Hence, each student needs to know that “the more papers you submit, the more “accept” you get”. This statement is true regardless of which venues the student targets for. Furthermore, the value p (i.e., the probability of acceptance) can increase once students submit more papers to top-tier venues (by obtaining meaningful comments and gaining more experience). Therefore, every student should aim to submit papers to top-tier venues.
6.6 Never Give Up
Many students can get a lot of rejections for each of their research papers until they make that paper accepted in the conference/journal. Normally, there are three kinds of attitudes for those students once they receive a rejection notification (see Fig. 6.8). First, some students may think that this is the end of the world and have a doubt for whether they are suitable to be a qualified researcher. They will give up very easily (i.e., have no passion for doing anything related to research). Ultimately, they will leave the academia after graduation (some of them may even give up their postgraduate degrees). Second, some (“better”) students may be willing to submit that paper. But they choose some second-tier or third-tier venues (a.k.a. easy venues). Ultimately, no university wants to hire them after graduation because of the concern for whether they can conduct good research. Third, the best students insist for submitting papers to top-tier venues (no matter how many rejections they receive). Only these students can get a lot of top-tier papers after graduation and can be recruited by a top university/research lab.
Fig. 6.8
A productive student keeps submitting papers to top-tier venues no matter how many “Reject” they receive
To the first two types of research students, we would like to emphasize that the acceptance rate of top-tier venues is only 15–30% (as discussed in Sect. 6.5). Since the probability of acceptance is lower than 0.5, you need to expect that each research paper can be rejected for each submission. Despite this, each paper can ultimately be accepted once you keep submitting it based on the following probability concept.
Fig. 6.9
The first author of this book gets five times of rejection and ultimately manages to get the acceptance from ICDE 2025 for one of his research papers
Suppose that the probability of acceptance for each submission is p (where \(p > 0\)). The probability of acceptance in the ith submission is \((1-p)^{i-1}p\) (i.e., get rejections for \(i-1\) times and get acceptance for the ith time). Therefore, the probability of acceptance for a paper when the student keeps submitting it to top-tier venues is expressed as follows.
With this expression, if the student keeps submitting one paper, that paper must be ultimately accepted as long as the probability of acceptance for each submission p is not zero. This expression holds regardless of which venue the student targets for. As an example, although p can be smaller for a top-tier venue, the probability of acceptance is still 1 if the student keeps submitting that paper. Based on this reason, each student should choose top-tier venues for submission. Figure 6.9 illustrates an example for how the first author of this book submits the paper (regarding the efficient algorithms for spatiotemporal kernel density visualization) to top-tier venues. He finished this work in July 2022 and submitted this paper to SIGMOD 2023. The reviewers were negative about this work and gave a reject for it. He kept revising this paper (the title was changed) and submitted it to VLDB 2023 in December 2022 but it was still rejected. He did not give up and submitted it to SIGMOD 2024 and then ICDE 2024 (the title was changed again.) and was rejected again and again. He further revised the paper (the title was changed again.) and submitted it to TKDE 2024 and was still rejected. Lastly, he submitted it to ICDE 2025. This time, he got an acceptance in November 2024 for this paper. We believe that many students (or even faculty members) may have already given up this paper if they have received many rejections for one paper. This example shows that we should never give up. The paper must be accepted in top-tier venues if we keep revising and submitting it.
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