Converting a date/time to time_t using FxGqlC (or SQL)

The time_t is used in C++ to represent a date/time.  It is expressed in seconds since Januari 1st, 1970.

To get the current date/time as a time_t value, you can run this query in FxGqlC (or SQL):
select datediff(second, '1970-01-01', getutcdate())

You need to use getutcdate() because time_t defines the UTC time.

Or for any arbitrary date/time (in UTC):
select datediff(second, '1970-01-01', '2012-10-18 22:33') 
-- Returns 1350599580

The other way around is also easy: run this query to convert a time_t to a date/time
select dateadd(second, 1234567890, '1970-01-01')
-- Returns 13/02/2009 23:31:30

Ngram Viewer 2.0

Posted by Jon Orwant, Engineering Manager

Since launching the Google Books Ngram Viewer, we’ve been overjoyed by the public reception. Co-creator Will Brockman and I hoped that the ability to track the usage of phrases across time would be of interest to professional linguists, historians, and bibliophiles. What we didn’t expect was its popularity among casual users. Since the launch in 2010, the Ngram Viewer has been used about 50 times every minute to explore how phrases have been used in books spanning the centuries. That’s over 45 million graphs created, each one a glimpse into the history of the written word. For instance, comparing flapper, hippie, and yuppie, you can see when each word peaked:

Meanwhile, Google Books reached a milestone, having scanned 20 million books. That’s approximately one-seventh of all the books published since Gutenberg invented the printing press. We’ve updated the Ngram Viewer datasets to include a lot of those new books we’ve scanned, as well as improvements our engineers made in OCR and in hammering out inconsistencies between library and publisher metadata. (We’ve kept the old dataset around for scientists pursuing empirical, replicable language experiments such as the ones Jean-Baptiste Michel and Erez Lieberman Aiden conducted for our Science paper.)

At Google, we’re also trying to understand the meaning behind what people write, and to do that it helps to understand grammar. Last summer Slav Petrov of Google’s Natural Language Processing group and his intern Yuri Lin (who’s since joined Google full-time) built a system that identified parts of speech—nouns, adverbs, conjunctions and so forth—for all of the words in the millions of Ngram Viewer books. Now, for instance, you can compare the verb and noun forms of “cheer” to see how the frequencies have converged over time:

Some users requested the ability to combine Ngrams, and Googler Matthew Gray generalized that notion into what we’re calling Ngram compositions: the ability to add, subtract, multiply, and divide Ngram counts. For instance, you can see how “record player” rose at the expense of “Victrola”:

Our info page explains all the details about this curious notion of treating phrases like components of a mathematical expression. We’re guessing they’ll only be of interest to lexicographers, but then again that’s what we thought about Ngram Viewer 1.0.

Oh, and we added Italian too, supplementing our current languages: English, Chinese, Spanish, French, German, Hebrew, and Russian. Buon divertimento!

LibreOffice doesn't appear in alt-tab view

I have an annoying problem with Unity on Ubuntu: it often happens that LibreOffice/OpenOffice Calc or Writer windows don't appear in the alt-tab application switching.
Googling the problem learned me that it is a known problem: https://bugs.launchpad.net/bamf/+bug/1026426
The good news is that it is solved in Ubuntu 12.10, and a patch will be available for 12.04 LTS. A workaround is to restart Unity:

• Start a command window (Ctrl-Alt-T)
• Run:
  unity --replace & disown

ReFr: A New Open-Source Framework for Building Reranking Models

Posted by Dan Bikel and Keith Hall, Research Scientists at Google

We are pleased to announce the release of an open source, general-purpose framework designed for reranking problems, ReFr (Reranker Framework), now available at: http://code.google.com/p/refr/.

Many types of systems capable of processing speech and human language text produce multiple hypothesized outputs for a given input, each with a score. In the case of machine translation systems, these hypotheses correspond to possible translations from some sentence in a source language to a target language. In the case of speech recognition, the hypotheses are possible word sequences of what was said derived from the input audio. The goal of such systems is usually to produce a single output for a given input, and so they almost always just pick the highest-scoring hypothesis.

A reranker is a system that uses a trained model to rerank these scored hypotheses, possibly inducing a different ranked order. The goal is that by employing a second model after the fact, one can make use of additional information not available to the original model, and produce better overall results. This approach has been shown to be useful for a wide variety of speech and natural language processing problems, and was the subject of one of the groups at the 2011 summer workshop at Johns Hopkins’ Center for Language and Speech Processing. At that workshop, led by Professor Brian Roark of Oregon Health & Science University, we began building a general-purpose framework for training and using reranking models. The result of all this work is ReFr.

From the outset, we designed ReFr with both speed and flexibility in mind. The core implementation is entirely in C++, with a flexible architecture allowing rich experimentation with both features and learning methods. The framework also employs a powerful runtime configuration mechanism to make experimentation even easier. Finally, ReFr leverages the parallel processing power of Hadoop to train and use large-scale reranking models in a distributed computing environment.

EMEA Faculty Summit 2012

Michel Benard, University Relations Manager

Last week we held our fifth Europe, Middle East and Africa (EMEA) Faculty Summit in London, bringing together 94 of EMEA’s foremost computer science academics from 65 universities representing 25 countries, together with more than 60 Googlers.

This year’s jam-packed agenda included a welcome reception at the Science Museum (plus a tour of the special exhibition: “Codebreaker - Alan Turing’s life and legacy”), a keynote on “Research at Google” by Alfred Spector, Vice President of Research and Special Initiatives and a welcome address by Nelson Mattos, Vice President of Engineering and Products in EMEA, covering Google’s engineering activity and recent innovations in the region.

The Faculty Summit is a chance for us to meet with academics in Computer Science and other areas to discuss the latest exciting developments in research and education, and to explore ways in which we can collaborate via our our University Relations programs.

The two and a half day program consisted of tech talks, break out sessions, a panel on online education, and demos. The program covered a variety of computer science topics including Infrastructure, Cloud Computing Applications, Information Retrieval, Machine Translation, Audio/Video, Machine Learning, User Interface, e-Commerce, Digital Humanities, Social Media, and Privacy. For example, Ed H. Chi summarized how researchers use data analysis to understand the ways users share content with their audiences using the Circle feature in Google+. Jens Riegelsberger summarized how UI design and user experience research is essential to creating a seamless experience on Google Maps. John Wilkes discussed some of the research challenges - and opportunities - associated with building, managing, and using computer systems at massive scale. Breakout sessions ranged from technical follow-ups on the talk topics to discussing ways to increase the presence of women in computer science.

We also held one-on-one sessions where academics and Googlers could meet privately and discuss topics of personal interest, such as how to develop a compelling research award proposal, how to apply for a sabbatical at Google or how to gain Google support for a conference in a particular research area.

The Summit provides a great opportunity to build and strengthen research and academic collaborations. Our hope is to drive research and education forward by fostering mutually beneficial relationships with our academic colleagues and their universities.

Running Continuous Geo Experiments to Assess Ad Effectiveness

Posted by Jon Vaver, Research Scientist and Lizzy Van Alstine, Marketing Manager

Advertisers have a fundamental need to measure the effectiveness of their advertising campaigns. In a previous paper, we described the application of geo experiments to measuring the impact of advertising on consumer behavior (e.g. clicks, conversions, downloads). This method involves randomly assigning experimental units to control and test conditions and measuring the subsequent impact on consumer behavior. It is a practical way of incorporating the gold standard of randomized experiments into the analysis of marketing effectiveness. However, advertising decisions are not static, and the original method is most applicable to a one-time analysis. In a follow-up paper, we generalize the approach to accommodate periodic (ongoing) measurement of ad effectiveness.

In this expanded approach, the test and control assignments of each geographic region rotate across multiple test periods, and these rotations provide the opportunity to generate a sequence of measurements of campaign effectiveness. The data across test periods can also be pooled to create a single aggregate measurement of campaign effectiveness. These sequential and pooled measurements have smaller confidence intervals than measurements from a series of geo experiments with a single test period. Alternatively, the same confidence interval can be achieved with a reduced magnitude or duration of ad spend change, thereby lowering the cost of measurement. The net result is a better method for periodic and isolated measurement of ad effectiveness.

Power Searching with Google is back

Posted by Dan Russell, Uber Tech Lead, Search Quality & User Happiness

If you missed Power Searching with Google a few months ago or were unable to complete the course the first time around, now’s your chance to sign up again for our free online course that aims to empower our users with the tools and knowledge to find what they’re looking for more quickly and easily.

The community-based course features six 50-minute classes along with interactive activities and the opportunity to hear from search experts and Googlers about how search works. Beginning September 24, you can take the classes over a two-week period, share what you learn with other students in a community forum, and complete the course assessments to earn a certificate of completion.

During the course’s first run in July, people told us how they not only liked learning about new features and more efficient ways to use Google, but they also enjoyed sharing tips and learning from one another through the forums and Hangouts. Ninety-six percent of people who completed the course also said they liked the format and would be interested in taking similar courses, so we plan to offer a suite of upcoming courses in the coming months, including Advanced Power Searching.

Stay tuned for further announcements on those upcoming courses, and don’t forget to register now for Power Searching with Google. You’ll learn about things like how to search by color, image, and time and how to solve harder trivia questions like our A Google a Day questions. We’ll see you when we start up in two weeks!