Bhaumik Chokshi |
Liked
application of the methods and the analysis part of the projects; Liked the
idea of using anchor text for retrieving images. |
Bob Leaman |
Impressed by
how AI techniques can be used in real applications; liked the overtones of
the class discussion, such as the significance and impact of bias in machine
learning. Using domain
knowledge is important to make real application work. |
Chance Kirsch |
Liked social
networks for their application to many
web applications; Liked
information extraction; Wondered how
to come up with something better than the current search engines; |
Garrett Wolf |
Liked vector
similarity ranking model and LSI; Liked the
connection between image processing and clustering/classification problems; Interested in
scalability of the techniques; |
Hemal Khatri |
Liked the
discussion about DB/IR interaction; Interested in
how search engines can answer questions (as against retrieving documents) Interested in
topic specific search and personalized search; Search engine
should use more types of relevance feedback; |
Madhu Datla |
Felt that the
course went significantly beyond search engine techniques; Liked
information integration/extraction discussion; Liked the
connections between topics; |
Martin Lehner |
Liked social
network, folksonomies, NBC; Felt the
course is difficult since it brought together many different things such as
AI and DB; Interested in
more AI techniques; |
Mingyi Shu |
Liked vector
similarity ranking and PageRank, which are fundamental but very useful in
practice; Appreciated being
able to see the value of the techniques behind google/amazon; Liked the
discussion of information extraction and social networks; The course is
a combination of many different areas; Homework and
projects are difficult but helpful and interesting; |
Munmun De Choudhury |
Liked vector
similarity ranking; Liked LSI but
wondered why Google doesn’t use it; Enjoyed the
discussion on DB/IR interaction and using source statistics in query
processing; |
Nicholas Radtke |
Liked vector
similarity ranking and LSI; Felt that
pageRank makes questionable assumptions on the random surfing model; Would like to
see more clustering techniques beyond K-means; XML and XML
query languages are useful; Liked
folksonomy but the problem is how to get people to do it; Impressed by
how simple ideas work in real applications; |
Niyati Parikh |
Liked most
topics covered. Impressed by
how simple ideas such as vector similarity ranking can be so effective in
search; Liked
relevance feedback and wondered why it is not used in real search engines; Liked social
networks and wondered what other applications can take advantage of such
techniques; |
Siddharth Raghavan |
Liked social
networks and their applications in folksonomies etc.; Felt the
topics covered are very practical and liked to know the techniques behind
google/amazon; Liked the
applicability of the techniques in a wide range of domains; |
Syed Toufeeq
Ahmed |
Interested in
research on how to extract events and rare patterns; Interested in
how to broadcast information fast – connection with social networks |
Lei Tang |
Impressed by
how some unrealistic assumptions often works in real applications and
wondered what the truth/true hypothesis is behind the text documents; Would like to
know more about natural language processing and multimedia information
retrieval; |