CAP 6635: Artificial Intelligence (2022 Spring)
Course Report Instruction
(For students participating final exam) (10 points)
Due date [May 6 2022, Firm]
This instruction only applies to students who will participate the final exam (do NOT wish to
substitute the final exam using term project). If you wish to substitute the final exam using a
longer version of the term project report (i.e., a research report), please follow “Research
Report Instruction” (for students substituting final exam) in the Canvas.
The grading of the term project report is based on the following criteria.
1. Overall [2 pts]: You should organize your report in IEEE format, with 1000 words minimum. Please
note that table/figure do not count towards the word limitation. You can use IEEE word or Latex
temperate from the following URL
a. Template: http:
www.ieee.org/conferences_events/conferences/publishing/templates.html.
. Plagiarism: You cannot copy any sentences, paragraphs, or figures, from any external
sources (such as published papers or Internet). If Turnitin indicates that a submission is over
30% similar to any other submissions, the instructor will ca
y out a Plagiarism investigation.
c. If you have to cite a figure/graph published somewhere else, please properly cite the source of
the reference [0 credit if plagiarism check returns over 50% similarity to any published work].
[Grading of grammars and typos are included in the “Overall”]
2. Introduction [1 pt]: Your report must have an introduction section with about 200 words. The
introduction should clearly state (1) what is the research problem to be studied in the report (i.e., text
classification); (2) the motivation of the problem studied in your report; (3) how are the problem
solved by existing methods, if any; and (4) a
ief description about the method you will propose in
the report. [200 words]
3. Main body [3 pts]: In the body of your project, you will need to provide technical details of your
design [500 words]
a. You need to provide a
ief description about Bayesian Network. Then discussion how naïve
ayes classification is related to the Bayesian network.
. You will need to provide a
ief description about your learning/classification methods, the
enchmark datasets, and performance measures used in the study.
c. You need to show at least one figure (or diagram) of your framework.
4. Experiments [2 pts]: In the experiments, you need to introduce (1) main purpose of the experimental
studies; (2) what are the tools used to design the algorithms; (3) what are the baseline methods for
http:
www.ieee.org/conferences_events/conferences/publishing/templates.html
comparisons; and (4) what are the performance measures and data used for empirical studies. You
should also use figures and tables to report the results collected from your studies, and summarize the
experimental results [200 words].
a. Experimental settings: including programming tools/languages, the setting of the parameters
used for different methods. [1 pt]
. The results: The detailed results reported in figures/tables with necessary analysis and
descriptions. Your report must include at least one figure and one table to show the results. [1
pts]
5. Conclusions [1 pt]: In the conclusions, you should
iefly summarize the research problem studied in
your report. Explain what you have done and summarize the major findings. Draw any informative
conclusions, which can be useful to guide the followers [100 words, 1 point]
6. References [1 pt]: Please cite at least 5 relevant references in your report. At least 3 of them must be
from 2015 or after. [1 point].