Chapter 9 Conclusions and Future Work
9.2 Future Work
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The ACM Digital Library and IEEE Computer Society are adopted as databases for searching conference papers. These are two renowned academic communities within the domain of Computer science, and hold extensive collections of all formats of conference papers within their academic communities.
The ACM Digital Library, IEEE Computer Society, ProQuest and ScienceDirect Onsite were adopted as the four databases for the searching of journal papers. Thus, two extra databases were included to complement ACM Digital Library and IEEE Computer Society’s scarcity in journal collections, and to generalize our research findings, so that our deduction can be further expanded.
The titles of the papers were adopted as the benchmarks for our extraction of information in the first part of the study, since they are strongly representative of the entire article. But in the second part and third part we try to use the title and Abstract as our descriptor of the papers. TextAnalyst was utilized to analyze the words used in titles, and single out the ones that have been repeated more than three times as features of this research. It may have some limitations of its embedded algorithm in the tool.
The novel methods we proposed can improve the limitations of impact factor proposed by ISI. Besides, it uses the impact power of the authors and the publication in a topic to measure the impact power of a paper before it really has been an impact paper can solve the limitations of Google scholar’s approach. We suggest that the topic oriented thinking of our methods can really help the researchers to solve their problems of searching the valuable topics.
9.2 Future Work
The future work can focus on the four relationships between the conferences and journals. The single term or n-gram terms perhaps not sufficient enough to represent a topic. The combination of the terms or the other approach can represent the semantic meaning of the topics will improve the method. The descriptors and the keywords we use to search the database will limit the representation of the paper and research field.
Besides, the Bayesian estimation can evolution use the Markov Chain Monte Carlo (MCMC) method. In the proving the precise of the impact power, the cited frequency and published volume can determine the impact power of the authors or the publications. It makes sense that an author’s impact power can be the endorsement of a publication and vice versa. In the part of indices, it needs more information to improve the indices more feet the realty. The situations that if a real impact paper was not published by the impact author or publication and then it would not be detected in this method. Besides, the method we proposed will ignore the new but potential
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scholars since the method is based on the accumulative cited frequency. The field of a cite publication needs to be considered to figure out the real community which we exactly want to discuss in a topic. All the procedures and algorithm of academic intelligence in this dissertation can exactly combines to find out the emerging topics in someone’s research field. In the application point of view, the methods can also apply in the publishers such as Reuters or Washington Post for detecting whether an issue is too hot or not. It is also can apply in the stock index estimation to figure out whether the stock market is too hot or not. And we think researchers will get more creative ideas to apply the idea of this study in their research domain.
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Appendix A Questionnaire
Dear Professors:
Greetings. I am a Ph. D. candidate at National Chengchi University. This is a research questionnaire for my dissertation which is a study in the Academic Intelligence Involving Information Retrieval. The questionnaire uses a common topic of Data Mining to test the research model. The questionnaire is divided into three parts. They are (A) the emerging topics life cycle, (B) the impact power of authors, and (C) the impact power of publications. Thank you so much for your kind help, time and efforts.
Best regards,
Dr. Jia-Lang Seng
Distinguished Professor & Chair Dept & Graduate School of Accounting National Chengchi University
Dr. Woo-Tsong Lin Associate Dean College of Commerce
National Chengchi University Ph.D. Candidate Yi-Ning Tu
Department and Graduate School of Management Information Systems National Chengchi University
94356509@nccu.edu.tw
0916-075571
Part A : The Emerging Research Topics Life Cycle
Questions
Yes No
No Opinion
1. Do you agree the topic “Image Retrieval” is emerging from the year 2000?
2. Do you agree the topic “Sensor Network” is emerging from the year 2004?
3. Do you agree the topic “Semantic Web” is emerging from the year 2004?
4. Do you agree the topic “Support Vector” is emerging from the year 2004?
Opinions:
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Part B : The Impact Power of Authors in Data Mining (During 1990-2002)
Descriptions Yes No No Opinion
1 Bing Liu
2 Charu C. Aggarwal
3 Chris Clifton
4 David W. Cheung
5 Foster J. Provost
6 George Karypis
7 Hannu T. T. Toivonen
8 Heikki Mannila
9 Huan Liu
10 Jiawei Han
11 Kyuseok Shim
12 Ming-syan Chen
13 Mohammed Javeed Zaki 14 Osmar R. Zaïane
15 Philip S. Yu
16 Rajeev Rastogi
17 Rakesh Agrawal
18 Ron Kohavi
19 Salvatore J. Stolfo 20 Venkatesh Ganti
Part C : The Impact Power of Publications in Data Mining Part C1 : Journals list (During 1990-2002)
The title of the publications
Yes No No Opinion 1 Bioinformatics2 Communications of the ACM (CACM) 3 Data Mining and Knowledge Discovery
4 IEEE Bulletin of the Technical Committee on Data Engineering 5 IEEE Computers
6 IEEE Transactions on Knowledge and Data Engineering 7 IEEE Transactions on Visualization and Computer Graphics 8 Knowledge and Information Systems
9 Machine Learning 10 SIGKDD Explorations 11 SIGMOD Record
Opinions:
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Part C2 : Conferences list (During 1990-2002)
The title of the publications
Yes No No Opinion1 ACM Conference on Computers and Security 2 ACM International Conference on Digital Libraries
3 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
4 ACM Symposium on Principles of Database Systems 5 Advances in Digital Libraries Conference (ADL)
6 Advances in Distributed and Parallel Knowledge Discovery 7 Advances in Large Margin Classifiers
8 Advances in Neural Information Processing Systems (NIPS) 9 European Conference on Machine Learning (ECML)
10 Genetic and Evolutionary Computation Conference (GECCO)
11
IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
12 Industrial Conference on Data Mining (ICDM) 13 International Conference on Data Engineering (ICDE)
14 International Conference on Data Warehousing and Knowledge Discovery (DaWaK)
15 International Conference on Database Theory (ICDT)
16
International Conference on Information and Knowledge Management (CIKM)
17 Lecture Notes in Computer Sciences (LNCS) 18 Lecture Notes in Artificial Intelligence (LNAI)
19 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
20 Principles of Data Mining and Knowledge Discovery (PKDD) 21 SIAM International Conference on Data Mining (SDM) 22 SIGMOD
23
SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD)
24 Very Large DataBase (VLDB)
Opinions: