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Facebook Leaks Usernames, User IDs, and Personal Details to Advertisers

Browse Facebook, and you wouldn’t expect Facebook’s advertisers to learn who you are. After all, Facebook’s privacy policy and blog posts promise not to share user data with advertisers except when users grant specific permission.
But in my testi… → Read More: Facebook Leaks Usernames, User IDs, and Personal Details to Advertisers

TREC-BLOG – 2010 Guidelines

TREC-BLOG – 2010 Guidelines → Read More: TREC-BLOG – 2010 Guidelines

TREC-BLOG – 2010 Guidelines

TREC-BLOG – 2010 Guidelines → Read More: TREC-BLOG – 2010 Guidelines

People You May Know — Now With Faceted Search!

I was just looking at LinkedIn and found myself pleasantly surprised by a minor UI improvement in the “People You May Know” widget: as you delete people you don’t know, the widget now updates without your having to go to another page or refresh the home page. Curious, I looked to see if LinkedIn had [...] → Read More: People You May Know — Now With Faceted Search!

The Google Job Experiment

This is just so brilliant that I had to post it here. I’ve blogged in the past about alerting spam, but this guy took the idea to a new level, with great return on investment. Perhaps the news about this story will make the tactic more popular and thus less effective through dilution. Still, it’s [...] → Read More: The Google Job Experiment

Slides from Enterprise Search Summit Keynotes

Here are the slides from Marti Hearst’s and Peter Morville‘s keynote presentations at the Enterprise Search Summit: Designing Search For Humans Search & Discovery Patterns → Read More: Slides from Enterprise Search Summit Keynotes

Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Gordon V. Cormack, Mark D. Smucker, and Charles L. A. Clarke University of Waterloo The TREC 2009 web ad hoc and relevance feedback tasks used a new document collection, the ClueWeb09 dataset, which was crawled from the general Web in early 2009. This dataset contains 1 billion web pages, a substantial fraction of which are […] → Read More: Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Gordon V. Cormack, Mark D. Smucker, and Charles L. A. Clarke University of Waterloo The TREC 2009 web ad hoc and relevance feedback tasks used a new document collection, the ClueWeb09 dataset, which was crawled from the general Web in early 2009. This dataset contains 1 billion web pages, a substantial fraction of which are […] → Read More: Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Gordon V. Cormack, Mark D. Smucker, and Charles L. A. Clarke University of Waterloo The TREC 2009 web ad hoc and relevance feedback tasks used a new document collection, the ClueWeb09 dataset, which was crawled from the general Web in early 2009. This dataset contains 1 billion web pages, a substantial fraction of which are […] → Read More: Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Gordon V. Cormack, Mark D. Smucker, and Charles L. A. Clarke University of Waterloo The TREC 2009 web ad hoc and relevance feedback tasks used a new document collection, the ClueWeb09 dataset, which was crawled from the general Web in early 2009. This dataset contains 1 billion web pages, a substantial fraction of which are […] → Read More: Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets