Archive for the ‘conference’ Category

chi report 2010

Thursday, May 6th, 2010

i’ve just finished to attend a chi presentation/report from cambridge folks. two fantastic videos at the end. now, some papers of interest:

An unobtrusive behavioral model of “gross national happiness” - this could catch the attention of people working on happiness/mood/emotions ;-) check out the facebook application

Blogging in a region of conflict: supporting transition to recovery - one interesting finding:  “blogs enable people experiencing a conflict to engage in dialogue with people outside their borders to discuss their situation”

Microblogging during two natural hazards events: what twitter may contribute to situational awareness

Pensieve: supporting everyday reminiscence - “everyday reminiscence by emailing memory triggers to people that contain either social media content they previously created on third-party websites or text prompts about common life experiences.”

Useful junk?: the effects of visual embellishment on comprehension and memorability of charts (best paper) – how to present a graph? cool info-graphics in the paper ;-) and interesting analysis of precision of retrieving charts vs. recall after 3 weeks

Crowdsourcing graphical perception: using mechanical turk to assess visualization design - they repeated some info visualization experiments on mechturk

Applying reputation to science

Friday, February 12th, 2010

I was browsing old posts of MobBlog the other day, and ran into Daniele’s post on (double) blind review. I have to say I’ve yet to see a conference in my field which genuinely benefited from double blind review, and despite the anecdotes I’ve heard of double blind being statistically better for female authors than regular review, I’m starting to think we possibly need to move for the exact opposite soon. (more…)

ACM RecSys 2009 Keynote (in 140 character chunks)

Friday, October 23rd, 2009

The third ACM RecSys conference started today in New York; unfortunately I could not make it. However, a number of people who I follow on Twitter are there (@xamat, @danielequercia, @barrysmyth)… and are tweeting away as the conference unfolds. You can follow the stream of #recsys09 tweets here. Although I’m sure that there are many details that do not make it into the 140 character-long tweets, they provide a real time snapshot of what is going on in the conference.

For example, the first keynote has just ended. Francisco Martin, Founder/CEO Strands, gave a talk about the “Top 10 Lessons Learned Developing, Deploying, and Operating Real-World Recommender Systems.” Here’s the twitter summary (note: copy/pasted and lightly edited to merge similar tweets).

Lesson 1 – Make sure a recommender is really needed! Do you have lots of recommendable items? Many diverse customers?… also think Return-on-Invesment… a more sophisticated recommender may not deliver a better ROI.

Lesson 2 – Make sure the recommendations make strategic sense. Is the best recommendation for the customer also the best for the business? What is the difference between a good and useful recommendation? Good recommendations vs useful recs; Obvious recommendations may not be useful; risky recs may deliver better long-term value

Lesson 3 - Choose the right partner! Select the right rec vendor vs hire some #recsys09 students. If you are a big company the best you can do is to organize a contest

Lesson 4 – Forget about cold-start problems (!) …. just be creative. The internet has the data you need (somewhere…)

Lesson 5 – Get the right balance between data and algorithms. 70% of the success of a #recsys is on the data, the other 30% on the algorithm

Lesson 6 – Finding correlated items is easy but deciding what, how, and when to present to the user is hard… or dont just recommend for the sake of it. Remember user attention is a scarce and valuable resource. Use it wisely! … dont make a recommendations to a customer who is just about to pay for items at the checkout! User interface should get at least 50% of your attention.

Lesson 7 – Dont’s waste time computing nearest neighbours (use social connections)… just mine the social graph. Might miss useful connections??

Lesson 8 – Dont wait to scale

Lesson 9 – Choose the right feedback mechanism. Stars vs thumbs …. the YouTube problem. More research on implicit and other feedback mechanisms is needed. The perfect rating system is no rating system! … focus on the interface. Seems to me this is one of the gaps in current research… algorithms > data > interface

Lesson 10 – Measure Everything! … business control and analytics is a big opportunity here.

Keynote Takeaway – Think about application context; Focus on interface as much as algs; Be creative with startup data. … the UI needs to get the lion’s share of the effort (50%) compared to algorithms (5%) , knowledge (20%), analytics (25%)

SIGIR ’09

Tuesday, July 28th, 2009

Placing Flickr Photos on a Map. They place photos on a map based only on the tags of those photos. They exploit both info from nearby locations and spatial ambiguity

When More Is Less: The Paradox of Choice in Search Engine Use. They show that increasing recall works counter to user satisfaction, if it implies a choice from a more extensive set of result items. They call this phenomenon the paradox of choice. For example, having to choose from six results yielded both higher satisfaction and greater confidence than when there were 24 items to choose from

Telling Experts from Spammers: Expertise Ranking in Folksonomies. They presented a method in which power early-adopters  score highly. I call power early-adopters those who promptly tag items that happen to then become popular in the future.

Good Abandonment in Mobile and PC Internet Search. ” Investigation of when search abandonment is good (when the answer is right in the results list – no need to open page). Good abandonments are much more likely to occur on mobile device as opposed to PC; varies by locale (looked at US, Japan, China) and by category of query. “Our study has three key findings: First, queries potentially indicating good abandonment make up a significant portion of all abandoned queries. Second, the good abandonment rate from mobile search is significantly higher than that from PC search, across all locales tested. Third, classified by type of information need, the major classes of good abandonment vary dramatically by both locale and modality.”

Page Hunt: Improving Search Engines Using Human Computation Games. Microsoft Game Helps Make Search Better
Called Page Hunt, the game presents players with web pages and asks them to guess the queries that would produce the page within its first five results. Players score 100 points if the page is no.1 on the list, 90 points if it’s no.2, and so on. Bonuses are also awarded for avoiding frequently-used queries.

danah boyd’s gave a GREAT talk titled ‘The Searchable Nature of Acts in Networked Publics‘. In it, she debunked 3 myths about social networks:
1. There is only one type of social network. NO! There are 3 types of net
1) sociological network  (created from sociological study)
2) articulated network (created from listing friends)
3) behavioral network (created from interaction patterns)
those nets are very different but we have a tendency to assume they’re the same thing!!!

[Student Project Idea] Test whether the 3 types of social networks are related to each other and, if so, how!

2. Social ties are all equal. NO. The context of those ties and how strong they are are two important aspects, for example. (we have been discussing why context matters)
3. Content is King. In the tweet ‘i’m having for breakfast…’, the content isn’t important at all – it’s all about the awareness of sharing an experience.
danah then argued that social network sites are a type of networked public with four properties that are not typically present in face-to-face public life: persistence (what you say online it stays online), replicability (content can be duplicated (and can be taken of out-of-context – often u can’t replicate context)), searchability ( the potential visibility of content is great), and invisible audiences (we can only imagine the audience).  This networked public creates a new sense of what is public and what is private. For example, young people care deeply about their privacy, but their notion of privacy is very different from that of audults. finally,  danah introduced few stats on twitter (5% of accounts are protected, 22% include http://, 36% mention @user, 5% contain #hashtag, RT 3% are retweets, & spam accounts are proliferating) and highlighted some interesting research points for the future: 1)  how to make sense of content for such small bits of text; and 2) how social search can exploit analysis of the  network of twitters,  of context, and of tie strength.

IREVAL ’09: Workshop on the Future of IR Evaluation

Monday, July 27th, 2009

I recently attended the SIGIR ’09 IREVAL workshop on the future of IR evaluation, where I presented a poster on evaluating collaborative filtering over time. The workshop began with invited talks from (IR-research superstars) Stephen Robertson, Susain Dumais, Chris Buckley (videolectures), and Georges Dupret, giving talks that drew on years of research experience. The workshop participants then broke into groups to discuss different proposals related to IR-evaluation, and the workshop closed with a group discussion about each proposal. As can be expected, this workshop brought up many more questions than it answered. Below I’ve transcribed some notes that I took during the day:

(more…)

Recommender Systems @ SIGIR 2009

Friday, July 24th, 2009

There were two sessions on recommender systems at this year’s ACM SIGIR (held in Boston). Overall, it was a good conference- organised well, run smoothly. It became very quickly apparent to me (a first-timer to SIGIR) that this is a tight community of researchers; there were many hugs at the opening drinks. Here is a quick summary of the recommender system papers and a couple other noteworthy papers/events.

(more…)

IJCAI ’09 Workshop on Intelligent Techniques for Web Personalization & Recommender Systems

Sunday, July 12th, 2009

Yesterday, I attended the 7th IJCAI Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, in Pasadena. The IJCAI-2009 technical program will start on Tuesday. Here’s a summary of the sessions during the day: (more…)

Workshop on Complex Networks in Information & Knowledge Management (CNIKM)

Thursday, July 2nd, 2009

Dell Zhang of Birkbeck  sent us a CFP for this workshop in conjunction with ACM CIKM-2009, Hong Kong, November 6, 2009.  Paper submission: July 20th!

socialcom09

Monday, June 29th, 2009

The program of SocialCom is out. My picks:

  • Deriving Expertise Profiles From Tags (adriana.budura@epfl.ch)
  • Ranking Comments on the Social Web (khabiri@cse.tamu.edu)
  • Structure of Heterogeneous Networks (lerman@isi.edu)
  • Online User Activities Discovery based on Time Dependent Data (csdhong@cse.ust.hk)
  • Evaluating the Impact of Attacks In Collaborative Tagging Environments (mramezani@cdm.depaul.edu)
  • Community Computing: Comparisons between Rural and Urban Societies using Mobile Phone Data (nathan@mit.edu)

sigmond09 papers

Monday, June 15th, 2009

Temporal Collaborative Filtering

Tuesday, April 28th, 2009

As part of my recent work on collaborative filtering (CF), I’ve been examining the role that time plays in recommender systems. To date, the most notable use of temporal information (if you’re familiar with the Netflix prize) is that researchers are using time(stamps) to inch their way closer to the million dollar reward. The idea is to use how user-ratings vary according to, for example, the day of the week they were input in order to better predict the probe (and more importantly, the qualifying) datasets. I suppose my only criticism here is that once the million dollars has been won, nobody is going to implement and deploy this aspect of the algorithm (unless you are prepared to update your recommendations every day?) – since, in practice, we do not know when users are going to rate items.

In the context of my work, I’ve been looking at 2 areas; the effect of time on (1) similarity between users (RecSys ’08), and (2) the recommender system itself. Here’s a brief summary of (2): (more…)

Trust, Risk, Reputation and Recommendation on the Web

Monday, March 30th, 2009

I’m in the PC of this workshop. Please consider to submit your paper by April 27th.  The invited lecture will be given by Christian Maar, CIO of the Allegro Group, which is the leading provider of online auction services across Eastern and Central Europe.

Part of Christian’s talk will be about real problems of trust and reputation management for their online auction services.

blind review

Wednesday, March 18th, 2009

There are plenty of conferences that dropped blind reviewing and that consequently became cliquey (always the same people publish in them; more specifically, the match between “program committee” and “conference program” is surprising). The result: slack conferences. So I don’t really understand why a conference that was successfully growing should do this:

“RecSys ’09 will not use blind review”

boh!

27 Things To Do Before a Conference

Monday, March 16th, 2009

Here

The Internet for Activists

Friday, March 13th, 2009

When: Saturday 14th March 2009 (TOMORROW); 10am-5pm.

Where: @ SOAS

The Internet for Activists conference  will bring together activists and internet experts to help progressive campaigners to fight for change both on and offline. The program includes the following topics: Internet Security; Widgets & micro-blogging; Blogging for Building Campaigns; and Effective Online Campaigning (Success Stories).