Continuous Assessment Overview
| Module 7 KAN Min-Yen |
| Grading Metric: | |
| Average: | |
| Std. Dev: | |
| Disputes on grade should be brought up by the end of this week |
| Need a clear formulation of the problem: | |||
| Scope of the problem | |||
| Limit what you are going to examine | |||
| Be precise about what you are going to tackle | |||
| Motivation - reason why applicable to DL | |||
| A reasonably detailed idea of how you will approach the problem | |||
| How would one evaluate your project? | |||
| 24 Sep: Today | ||
| 2 week interval: have a clear idea what your project is going to be | ||
| 15 – 22 Oct: lecture presentation (done in pairs, sign up during break) | ||
| 2 week interval: have finished the bulk of the programming, and thought about how to evaluate your work | ||
| 13 Nov (Thursday, from 1-5 pm): final presentation | ||
| HENDRA SETIAWAN & EDWARD WIJAYA (Mixed-media Mining in DL) | |
| LIN LI & WONG SWEE SEONG (Document Clustering for DLs) | |
| HUANG WENDONG & WANG GANG (Music & Speech in Digital Libraries) | |
| LI YINGGUANG & VOROBIEV ARTEM (Peer to Peer in DLs) | |
| GUO SHUQIAO & YANG HUI (Web/Hypertext Information Seeking) | |
| MASLENNIKOV MSTISLAV & CHAN YEE SENG (Spatial and Temporal DLs) | |
| QIU LONG & TOK WEE HYONG (Intelligent Agents in DLs) | |
| CHEN XI & WANG XIAOHANG (Metadata Extraction and Indexing) | |
| Grade will depend more on quality, ideas, crisp results than number of hours spent | |||
| Creativity in defining the problem to be investigated | |||
| Quality of the methods used investigating it | |||
| Thoroughness in justifying your design decisions | |||
| Quality of your write-up | |||
| Reporting methods, results, discussion, etc. | |||
| Quality of evaluation of your system | |||
| You will not be penalized if your system performs poorly | |||
| Try to make it something that shows something interesting, not just an exercise in programming | ||
| But it can be a small something – be focused and not too ambitious | ||
| A clear research question or application, and hypotheses about a good approach to it | ||
| A clear and complete discussion of the theory / algorithms / method used | ||
| A high-level description of the implementation | ||
| Testing, and discussion of results | ||
| Clear graphs, tables, experimental comparisons | ||
| A discussion of alternatives and their performance | ||
| Brief but adequate discussion of related work | ||
| Idea’s motivation, originality, scoping: 25% | ||
| A chance for you to refine your proposal | ||
| Experiment methods, implementation: 25% | ||
| Evaluation methods, results and post-analysis: 25% | ||
| Quality of write-up | ||
| Including adequate comparison to prior work, proper citing: 25% | ||
| This part should be easy since you have done the survey paper | ||
| Bibliometrics | |
| Citation typing and visualization | |
| Pagerank | |
| HITS |