Summary of My First Trip to Strata #strataconf

In this post I am goIing to summarize some of the things that I learned at Strata Santa Clara 2013. For now, I will only discuss the conference sessions as I have a much longer post about the tutorial sessions that I am still working on and will post at a later date. I will add to this post as the conference winds down.

The slides for most talks will be available here but not all speakers will share their slides.

This is/was my first trip to Strata so I was eagerly awaiting participating as an attendant. In the past, I had been put off by the cost and was also concerned that the conference would be an endless advertisement for the conference sponsors and Big Data platforms. I am happy to say that for the most part I was proven wrong. For easier reading, I am summarizing talks by topic rather than giving a laundry list schedule for a long day and also skip sessions that I did not find all that illuminating. I also do not claim 100% accuracy of this text as the days are very long and my ears and mind can only process so much data when […]

Adventures at My First JSM (Joint Statistical Meetings) #JSM2012

During the past few decades that I have been in graduate school (no, not literally) I have boycotted JSM on the notion that “I am not a statistician.” Ok, I am a renegade statistician, a statistician by training. JSM 2012 was held in San Diego, CA, one of the best places to spend a week during the summer. This time, I had no excuse not to go, and I figured that in order to get my Ph.D. in Statistics, I have to have been to at least one JSM. […]

Parsing Wikipedia Articles: Wikipedia Extractor and Cloud9

Lately I have doing a lot of work with the Wikipedia XML dump as a corpus. Wikipedia provides a wealth information to researchers in easy to access formats including XML, SQL and HTML dumps for all language properties. Some of the data freely available from the Wikimedia Foundation include

article content and template pages article content with revision history (huge files) article content including user pages and talk pages redirect graph page-to-page link lists: redirects, categories, image links, page links, interwiki etc. image metadata site statistics

The above resources are available not only for Wikipedia, but for other Wikimedia Foundation projects such as Wiktionary, Wikibooks and Wikiquotes.

As Wikipedia readers will notice, the articles are very well formatted and this formatting is generated by a somewhat unusual markup format defined by the MediaWiki project. As Dirk Riehl stated:

There was no grammar, no defined processing rules, and no defined output like a DOM tree based on a well defined document object model. This is to say, the content of Wikipedia is stored in a format that is not an open standard. The format is defined by 5000 lines of php code (the parse function of MediaWiki). That code may […]

LexisNexis Open-Sources its Hadoop Alternative

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SIGKDD 2011 Conference — Days 2/3/4 Summary

<< My review of Day 1.

I am summarizing all of the days together since each talk was short, and I was too exhausted to write a post after each day. Due to the broken-up schedule of the KDD sessions, I group everything together instead of switching back and forth among a dozen different topics. By far the most enjoyable and interesting aspects of the conference were the breakout sessions.

Keynotes

KDD 2011 featured several keynote speeches that were spread out among three days and throughout the day. This year’s conference had a few big names.

Steven Boyd, Convex Optimization: From Embedded Real-Time to Large-Scale Distributed. The first keynote, by Steven Boyd, discussed convex optimization. The goal of convex optimization is to minimize some objective function given linear constraints. The caveat is that the objective function and all of the constraints must be convex (“non-negative curvature” as Boyd said). The goal of convex optimization is to turn the problem into a linear programming problem. We should care about convex optimization because it comes from some beautiful and complete theory like duality and optimality conditions. I must say, that whenever I am chastising statisticians, I often say that all they […]

SIGKDD 2011 Conference — Day 1 (Graph Mining and David Blei/Topic Models)

I have been waiting for the KDD conference to come to California, and I was ecstatic to see it held in San Diego this year. AdMeld did an awesome job displaying KDD ads on the sites that I visit, sometimes multiple times per page. That’s good targeting!

Mining and Learning on Graphs Workshop 2011

I had originally planned to attend the 2-day workshop Mining and Learning with Graphs (MLG2011) but I forgot that it started on Saturday and I arrived on Sunday. I attended part of MLG2011 but it was difficult to pay attention considering it was my first time waking up at 7am in a long time. The first talk I arrived for was Networks Spill the Beans by Lada Adamic from the University of Michigan. Adamic’s presented work involved inferring properties of content (the “what”) using network structure alone (using only the “who”: who shares with whom). One example she presented involved questions and answers on a Java programming language forum. The research problem was to determine things such as who is most likely to answer a Java beginner’s question: a guru, or a slightly more experienced user? Another research question asked what dynamic interactions tell us […]

Hadoop Fatigue — Alternatives to Hadoop

It’s been a while since I have posted… in the midst of trying to plow through this dissertation while working on papers for submission to some conferences.

Hadoop has become the de facto standard in the research and industry uses of small and large-scale MapReduce. Since its inception, an entire ecosystem has been built around it including conferences (Hadoop World, Hadoop Summit), books, training, and commercial distributions (Cloudera, Hortonworks, MapR) with support. Several projects that integrate with Hadoop have been released from the Apache incubator and are designed for certain use cases:

Pig, developed at Yahoo, is a high-level scripting language for working with big data and Hive is a SQL-like query language for big data in a warehouse configuration. HBase, developed at Facebook, is a column-oriented database often used as a datastore on which MapReduce jobs can be executed. ZooKeeper and Chukwa Mahout is a library for scalable machine learning, part of which can use Hadoop. Cascading (Chris Wensel), Oozie (Yahoo) and Azkaban (LinkedIn) provide MapReduce job workflows and scheduling.

Hadoop is meant to be modeled after Google MapReduce. To store and process huge amounts of data, we typically need several machines in some cluster configuration. A distributed […]

My Review of Hadoop Summit 2011 #hadoopsummit

I woke up early and cheery Wednesday morning to attend the 2011 Hadoop Summit in Santa Clara, after a long drive from Los Angeles and the Big Data Camp that lasted until 10pm the night before. Having been to Hadoop Summit 2010, I was interested to see how much of the content in the conference had changed.

This year, there were approximately 1,600 participants and the summit was moved a few feet away to the Convention Center rather than the Hyatt. Still, space and seating was pretty cramped. That just goes to show how much the Hadoop field has grown in just one year.

Keynotes

We first heard a series of keynote speeches which I will summarize. The first keynote was from Jay Rossiter, SVP of the Cloud Platform Group at Yahoo. He introduced how Hadoop is used at Yahoo, which is fitting since they organized the event. The content of his presentation was very similar to last year’s. One interesting application of Hadoop at Yahoo was for “retiling” the map of the United States. I imagine this refers to the change in aerial imagery over time. When performed by hand, retiling took 6 weeks; with Hadoop, it took […]

Big Data Camp 2011 #BigDataCamp

It has been a while since I have been to Silicon Valley, but Hadoop Summit gave me the opportunity to go. To make the most of the long trip, I also decided to check out BigDataCamp held the night before from 5:30 to 10pm. Although the weather was as predicted, I was not prepared for the deluge of pouring rain in the end of June. The weather is one of the things that is preventing me from moving up to Silicon Valley.

The food/drinks/networking event must have been amazing because it was very difficult to get everyone to come to the main room to start the event! We started with a series of lightning talks from some familiar names and some unfamiliar ones.

Chris Wensel, the developer of Cascading, is also the founder of Concurrent, Inc. Cascading is an alternate API for Map-Reduce written in Java. With Cascading, developers can chain multiple map-reduce jobs to form an ad hoc workflow. Cascading adds a built-in planner to manage jobs. Cascading usually infers Hadoop, but Cascading can run on other platforms including EMC Greenplum and the new MapR project. RazorFish and BestBuy use Cascading for behavioral targeting. Flightcaster uses a domain specific […]

Google — Is Search-by-Multimedia on the Way?

Recently, I have been thinking about alternate ways of specifying search queries other than with text. A couple of weeks ago I came across a piece of music that I could not identify. I thought it would be a huge win for a search engine to allow me to upload this piece, and it would present me with matches, or near matches to other pieces that sound similar, or have similar characteristics. Some services already exist. Shazam allows a user to place a microphone near playing music and it will identify the artist and song. Some uses of search-by-sound:

Music identification (“solved” – Shazam) Music personalizaton and recommendation (“solved” – Pandora) Identification of the source of a sound (i.e. a species of bird, a musical instrument, an inanimate object) MP3 and media file search Finding material that violates copyright

As our motivating example, consider we find some really cool graphic on the web and we want to know where it likely originated (i.e. art, a meme). In such a search engine, we could upload the graphic and get results containing the exact image, or images that are very similar such as variations of the image (crop, resize, borders, different effects), […]