Joint paper with Bing and Microsoft Research Accepted for Publication by CIKM 2013

August 12th, 2013 · No Comments

CIKM 2013The 2013 ACM International Conference on Information and Knowledge Management (CIKM) is one of the major forums for research on database management, information retrieval, and knowledge management. As such, we are proud to announce that our latest research paper, entitled “Understanding How People Interact with Web Search Results that Change in Real-Time Using Implicit Feedback,” co-authored with Jin Young Kim from Bing, Jaime Teevan from Microsoft Research and Dmitry Lagun from Emory University, has been accepted by the conference. Only 106 papers out of 848 submissions were selected, so the conference was very competitive.

The data once again demonstrates the extent to which dynamically ranking search results in response to real-time user feedback dramatically improves relevance:

Compared to traditional web search, users presented with dynamically ranked results exhibit higher engagement and find information faster, particularly during exploratory tasks. These findings have implications for how search engines might best exploit implicit feedback in real-time in order to help users identify the most relevant results as quickly as possible.

Enjoy the paper and if you attend the CIKM 2013 conference in San Francisco we look forward to seeing you there.

[Update – 2013-8-15] The paper may also be found on Jaime Teevan’s website at Microsoft Research.

[Update – 2013-9-9] We will be presenting during the Short Paper Session 52 – IR Track with is from 4-6:15pm on Thursday, October 31st.

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The T-shirts are in!

May 23rd, 2013 · 1 Comment

In celebration of the third patent issued to Surf Canyon by the USPTO, we designed some t-shirts! They arrived today. If you requested one, you will be receiving it shortly.

Team Surf Canyon models its latest designer wear

Team Surf Canyon models its latest designer wear

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USPTO Awards Third Patent to Surf Canyon

April 30th, 2013 · 1 Comment

USPTO LogoWe are delighted to announce that on Friday the USPTO awarded Surf Canyon its third patent, U.S. Patent No. 8,442,973, to be issued on May 14th, for “Real Time Implicit User Modeling for Personalized Search.” This is an important piece of intellectual property, as evidenced by the fact it has been referenced over 25 times by other patents issued to companies such as Google, Microsoft, Yahoo!, IBM and Samsung. The Abstract of the invention is as follows:

A method and apparatus for utilizing user behavior to immediately modify sets of search results so that the most relevant documents are moved to the top. In one embodiment of the invention, behavior data, which can come from virtually any activity, is used to infer the user’s intent. The updated inferred implicit user model is then exploited immediately by re-ranking the set of matched documents to best reflect the information need of the user. The system updates the user model and immediately re-ranks documents at every opportunity in order to constantly provide the most optimal results. In another embodiment, the system determines, based on the similarity of results sets, if the current query belongs in the same information session as one or more previous queries. If so, the current query is expanded with additional keywords in order to improve the targeting of the results.

Along with U.S. Patent No. 8,095,582 for “Dynamic Search Engine Results Employing User Behavior” and U.S. Patent No. 8,117,197 for “Adaptive User Interface for Real-Time Search Relevance Feedback,” the new patent rounds out Surf Canyon’s portfolio concerning the real-time re-ranking of search results in response to implicit user feedback.

To commemorate this momentous occasion, we have designed and will be giving away a special, universally loved item of tchotchke: t-shirts! You may check out our design and, should you like one for yourself, submit a request on the sign-up sheet. If you leave your address, we’ll do our best to get you one.


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Mention in University of Cambridge / Microsoft Paper on Personalization

February 1st, 2013 · No Comments

This paper, entitled “Personalizing Web Search using Long Term Browsing History,” was submitted to WSDM in 2011, but only recently came to our attention. The authors, Nicolaas Matthijs from the University of Cambridge and Filip Radlinski from Microsoft, write about “a user interest
profile using users’ complete browsing behavior,” but we thank them for taking a moment to recognize Surf Canyon’s contribution to the field:

Recently, personalized search has also been made available in some mainstream web search engines including Google and Yahoo!. These appear to use a combination of explicitly and implicitly collected information about the user. Many more companies are engaging in personalization both for search (e.g. and for advertising based on user behavior.

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Presentation at Bay Area Search Meetup

January 21st, 2013 · No Comments

Bay Area SearchMark Cramer, CEO of Surf Canyon, has been honored with an invitation to present Dynamic Ranked Retrieval at the next Bay Area Search Meetup. Anyone near the offices of eBay in San Jose on Wednesday, January 23rd, at 6:30pm, and who would like to attend, should click over to the Meetup website. Here is an Abstract of the talk:

Dynamic Ranked Retrieval – “Unsticking” the SERP

Search is stuck. And, frequently, so too are searchers.  The problem stems from the fact that, as Jaime Teevan described, “Web queries are very short, and it is unlikely that a two- or three-word query can unambiguously describe a user’s information goal.” Search engines respond to this by attempting to divine the user’s intent by exploiting massive quantities of data prior to delivering a static SERP, but the onus of either unambiguously describing the intent, or digging through pages of “best guesses,” often falls upon the user. This can be a daunting task depending on the searcher’s skill and knowledge of the subject matter as well as the clarity of the information need.

Dynamic Ranked Retrieval addresses this problem by creating a fluid SERP that re-ranks results “on the fly” in response to real-time implicit feedback from the user.  The strongest signals are the immediate ones, and the half-life of their informational value is extremely short, so waiting until a subsequent query to exploit them is deficient. Adapting the SERP dynamically to a real-time model of inferred user intent built from implicit feedback will maximize relevance and searcher satisfaction without requiring additional effort. We will demonstrate the technology and present real-world data on the impact to IR.

[Update 1/28/2013] The video from the presentation is now available online:

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Quick, yet Flattering, Mention in Computerworld

March 3rd, 2012 · No Comments

Stefan Hammon, writing an article for Computerworld about Google’s new privacy policy, had this to say:

“To be honest, I don’t google anymore. Search engines like Surf Canyon work just as well…”

We would point out that, for many queries, the innovative Dynamic Ranked Retrieval technology that we developed and embedded into our search page significantly improves the search experience over Google by automatically digging out relevant results for the user, but we are flattered nonetheless.

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Demo at SF Bay Area Firefox Add-ons Meetup Group

February 24th, 2012 · 1 Comment

Mark Cramer took a few minutes to present Surf Canyon’s Firefox Add-on at the SF Bay Area Firefox Add-ons Meetup Group’s last meeting.  Enjoy the whole thing or jump to the 36 minute mark to see the ~8 minute Surf Canyon demonstration.

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Search Visionary Joins Board of Advisors

January 24th, 2012 · No Comments

Having conducted early research into the strategies and benefits of Implicit User Modeling for Personalized Search, we are pleased to announce that ChengXiang Zhai, Associate Professor of Computer Science at the University of Illinois at Urbana-Champaign, has joined Surf Canyon’s Board of Advisers.

ChengXiang received his Ph.D. in Computer Science from Nanjing University in 1990 and another Ph.D. in Language and Information Technologies from Carnegie Mellon in 2002. His research interests include information retrieval, text mining, natural language processing, machine learning and bioinformatics, and he has published over 100 papers in major conferences and journals in these areas, including five award papers.

He is an Associate Editor of ACM Transactions on Information Systems and Information Processing and Management, and serves on the editorial board of the Information Retrieval Journal. He is a program co-chair of ACM CIKM 2004, NAACL HLT 2007 and ACM SIGIR 2009, where Mark Cramer was a presenter. He is an ACM Distinguished Scientist and has received many awards, including the 2004 Presidential Early Career Award for Scientists and Engineers (PECASE), the 2008 Alfred P. Sloan Research Fellowship, the 2007 Microsoft Beyond Search – Semantic Computing and Internet Economics Award, the 2009 IBM Faculty Award, the 2010 UIUC Rose Award for Teaching Excellence and the 2011 HP Innovation Research Award.

We are thrilled to have ChengXiang on the team as we look forward to exploring new avenues to improve the efficiency of information retrieval as well as continuing our collaboration with the UIUC.

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Cornell University Produces More Research on Dynamic Ranked Retrieval

January 18th, 2012 · 1 Comment

The research team at Cornell University, headed by Professor Thorsten Joachims, has produced another paper relating to Surf Canyon entitled “Structured Learning of Two-Level Dynamic Rankings.” It was presented on October 26, 2011 at CIKM in Glasgow. This paper further explores the concept of “Dynamic Ranked Retrieval” by proposing a two-level dynamic ranking model:

For ambiguous queries, conventional retrieval systems are bound by two conflicting goals. On the one hand, they should diversify and strive to present results for as many query intents as possible. On the other hand, they should provide depth for each intent by displaying more than a single result. Since both diversity and depth cannot be achieved simultaneously in the conventional static retrieval model, we propose a new dynamic ranking approach. In particular, our proposed two-level dynamic ranking model allows users to adapt the ranking through interaction, thus overcoming the constraints of presenting a one-size-fits-all static ranking.

Surf Canyon is again referenced, along with our 2009 SIGIR research paper:

We argue that a key to solving the conflict between depth and diversity lies in the move to dynamic retrieval models [2] that can take advantage of user interactions. Instead of presenting a single one-size-fits-all ranking, dynamic retrieval models allow users to adapt the ranking dynamically through interaction, as is done by [5].

In February 2008, Surf Canyon launched its Dynamic Ranked Retrieval application to rave reviews. As the body of research relating to Dynamic Ranked Retrieval grows, we continue to be encouraged by the potential of this technology to vastly enhance the quality of information retrieval.

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Expanding the Team

November 15th, 2011 · 1 Comment

This week Brandon McMullin started work at Surf Canyon as a Software Engineer. He will focus primarily on the development of our new social search application, Chummo.

In addition to his passion for software engineering, Brandon studies Shorinji Kempo, an art that focuses on personal improvement and the balance between strength and compassion. He is also a father. His 13-month-old daughter just recently gained some proficiency in walking and is intensely interested in exploring the world around her. She’s also very interested in daddy’s toys (like the laptop and Xbox controller) and has begun building structures with Mega Bloks. Clearly an engineer already in the making!

Our first hire in a few years, we’re thrilled to welcome Brandon to the team!

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