Suggestions for related pages could be algos that are used in NLP such as: word2vec, summarizer, etc.
Word segmentation edit: “This may be a difficult task as in some languages, like Chinese, the words are not separated by spaces.”
For each of the NPL tasks I would suggest linking each task to a different wiki page. Additionally, you could expand this section but having a definition and example for each of the tasks.
The first section of language models is a little awkward. I feel as if it needs more content. Also, some probabilities are in LaTeX and some are not. I would opt to keep things consistent.
I would say add more depth to the word2vec section so that it is similar to the N-Gram model section.
- The topic is relevant for the course. 5 (However it is very broad. To make it easier perhaps try to narrow the focus?)
- The writing is clear and the English is good. 5
- The page is written at an appropriate level for CPSC 522 students (where the students have diverse backgrounds). 5
- The formalism (definitions, mathematics) was well chosen to make the page easier to understand. 3 (there is some inconsistency, see above)
- The abstract is a concise and clear summary. 4 (I would add to it)
- There were appropriate (original) examples that helped make the topic clear. 5
- There was appropriate use of (pseudo-) code. 1 (need to add)
- It had a good coverage of representations, semantics, inference and learning (as appropriate for the topic). 5
- It is correct. 5
- It was neither too short nor too long for the topic. 2 (it is currently too short but it is apparent that it will be expanded)
- It was an appropriate unit for a page (it shouldn't be split into different topics or merged with another page). 3
- It links to appropriate other pages in the wiki. 3
- The references and links to external pages are well chosen. 5
- I would recommend this page to someone who wanted to find out about the topic. 4
- This page should be highlighted as an exemplary page for others to emulate. 5
If I was grading it out of 20, I would give it: 16