Dyer

 

JOHN 

·        Enjoyed most of collaborative  and content based filtering. Complimentary to each other, using both attributes and what users rated them.

·        Liked LSI, dim reduction, principal  component analysis, etc

·         Intrigued by how patterns can emerge in the data and use them to draw conclusions.

 

COMMISSO 

STEPHEN 

·        LSI was favorite, use of linear algebra, dimensionality reduction. How it affects information retrieval, synonymy, etc.

·        Automatically clustering.

·        Collaborative Filtering, how it actually works for amazon.

 

HOLLADAY 

BRYCE 

·        Surprised how a few matrix calculations can capture some of the semantic meaning of a text document. Reminds him of a friend that said that CS was based on math. Definitely true now.

o       Class shows cutting edge ways that you can solve problems with math.

·         The way google used link structure. Seems that you should always get your hands on all data you can.

·        Fact that clustering can be done automatically.

 

CIESIELSKI 

BRYAN 

·        A lot of the ideas are simple, but when web is brought in, then they can get much more complicated for scale issues.

o       Even in project it showed up.

·        Also interesting to note how many “fudge factors” are there in Google.

 

LIPP 

JOHN 

·        Originally didn't like LSI at all. Was one of those who slammed LSI in the first survey. But then he got matlab and sby using it, it started making sense in and got to like it.

o       Also LSI, used eigenvectors for image retrieval –a la Eigen Faces (by Kanav Kahol in the multi-media class)

HIRST 

HARVEY 

·        Enjoyed reading academic papers. It's missing when not reading those papers in other classes.

·        Figured out how bayes classification works for spam email software.

·        Preferred IR topics to II topics

 

SELLERS 

MICHAEL 

  ------AWOL--------------

 

ANDERSON 

CHRISTIAN 

·        Interesting to actually see some XML and use it. Used to be just a buzz word. Same with Xquery.

 

MCFADDEN 

MICHAEL 

·        Got to use math he learned. Got some meaning. Not just formulas and just crunching in numbers. Actual applications for the math. Also collaborative filtering.

 

FATNANI 

NIKHIL 

·        Regular communication between instructor and students. Website and mails.

·        Projects helpful to understand.

 

BALONEK 

BENJAMIN 

·        Professor was enthusiastic. In contrast to some other classes. Maybe just only 494 classes are like this.

·        Liked the  emails sent on the class list . Made him want to come to class.

·         Had no idea how Google worked. Now understands.

 

KALE 

SHREYAS 

·        How you can take basic text, categorize into matrices, and compute similarities, connection b/w docs, all this just mathematically.

·         Liked google paper, google-lecture.

·        Noticed how google kept on adding things, especially things that we said should be there.

·        Also yahoo paper (on using LSI clustering).

·         Structured data, xml because didn't know xml at all.

 

MARINICK 

JOHN 

Absent

 

 

 

 

 

 

FAN 

JIANCHUN 

·        Using simple mathematical models of text turns out to be working pretty well.

·         Cutting edge topics of the class. Especially last classes on combining DB and IR to help people find info more easily.

 

SINGHI 

SURENDRA 

·        Analysis in projects. Liked how ideas are simple but powerful in practice.

 

VADREVU 

SRINIVAS 

·        Liked power method for eigenvectors.

·        Discussion on Sabre database. Used to think expedia etc were already doing information integration.

·        Tyranny of majority.

·        DB & IR link.

 

ZHAO 

JICHENG 

·        Collaborative and, content based filtering.  Especially on how  to combine them with clustering.

·         Also clustering results of a search engine.

·        Topic specific pagerank.

 

BHIMAVARAPU 

RAVI 

·        LSI was most appealing.

·        Page Rank, structure of the web.

·        Content boosted collaborative filtering.

·        Database refresher by Ullas.

·        Thought first half was more interesting.

 

RYAN 

JOSHUA 

·        LSI and Page Rank.

·        Handling multi-dimensional vectors(?)

·        Liked the projects. Best in-class projects of ASU.

BENTON 

J 

·        Xqueries, and see how it works.

o       Even the fact that it existed.

·        Projects were great help in understanding what was done in class.

 

ASWATH 

DIPTI 

·        Clustering lectures.

·        DB and IR techniques.

·        Support of imprecise queries.

 

JANAKIRAMAN 

SHIVASHANKARI 

·        The fact that we focused on how new ideas could be applied.

o       Rather than just  on what has been done.

·        Like the slides a lot.

·        Projects required a lot of help and were a lot of fun.