Anyone familiar with Etsy knows that it is a fantastic website for finding handmade and vintage items, and a wonderful resource for gift-giving. Now, thanks to their search API and Surf Canyon’s dynamic ranking technology, there is an even better way to search through the millions of items for sale on Etsy. Click over to the Surf Canyon – Etsy Demo to try for yourself.
If you run a search for “gloves” on Etsy you’ll be presented with almost 70,000 results. There are facets on the left for drilling down, and of course users have the option of reformulating their queries to something more precise, but Surf Canyon has always been about alleviating the cognitive load by automatically and immediately assisting users with finding what they need.
As it so happens, tomorrow is Valentine’s Day, so perhaps the very first result fancies you, and so you select it. If your shopping is done, congratulations. It’s very rare indeed to find something to purchases with only a single click! More likely, however, you’ll return to the search page to check out more, which is when you’ll helpfully be provided with real-time recommendations from Surf Canyon’s dynamic ranking engine:
As you can see, these Valentine’s Day glove results are coming from pages 35, 37 and 41. It is hard to believe that anyone would ever dig that deep for a search result, but here they are helpful and automatically brought to page 1.
Every selection you make and every result you skip gives Surf Canyon’s dynamic search engine more information about your information need, enabling a superior ranking every step of the way. Clicking “More Results” on page 1 will produce more re-ranked results on page 1. Moving over to page 2 will the produce a second page of results tailored in real time to your needs.
In this particular example, you get more of what you want – gloves for Valentine’s Day:
The results are coming from pages 29, 23 and, somewhat amazingly, 88. Clicking a result on page 2 produces yet more re-ranked results, presented as “recommendations,” and the process continues.
Surf Canyon’s technology has been proven to deliver dramatic improvement in relevance, so give it a try!
The College Humor video below is NSFW, contains some profanity and mild sexual situations, but we’re posting it here because not only is it amusing, but it is an interesting insight into the relationship between users and search engines.
In their paper entitled “Beyond the Commons: Investigating the Value of Personalizing Web Search,” Teevan et al. state that, “Web queries are very short, and it is unlikely that a two- or three-word query can unambiguously describe a user’s informational goal.”
Simply put, it can be difficult for the user to accurately express what he or she is looking for with just a few words. Even with many words, depending on the type of query, it can be difficult to express what is ultimately desired from the results, regardless of whether the user is an expert in the domain or not. How many times in real life, speaking with real people, do people need to employ many words, over many sentences, to express a thought or need?
As a result, people will often ultimately end up fumbling and guessing with their search engine, which is humorously displayed in the video below.
We also figured someone must have done this before, but after searching online the code that we found was much longer and a lot more complicated (mainly because it was trying to access parts of the Etsy API that required OAuth authentication) than what we had been expecting. However, just doing a product search doesn’t require any authentication, so we went ahead and wrote some much simpler code that did only what we needed.
… a popular tool called Surf Canyon modifies SERPs for major search engines by surfacing as-yet unseen search results from deeper in the rankings every time the user clicks on a result link (the goal is for the surfaced results to be similar to the clicked result).
Their paper discusses how CrowdLogger, an open-source browser extension for Firefox and Google Chrome, can be used as an in situ evaluation platform for “evaluating retrieval systems in the wild.” This is something Surf Canyon has been doing with its own retrieval system for many years.
From the 1m40s mark to the 3m20s mark a screen shot of Surf Canyon is used to demonstrate dynamic ranking in action. Professor Joachims then offers DCG analysis of a sample search senario and concludes, at the 5m50s, that, “by being dynamic, and adaptive, you can gain a lot of retrieval performance.” Surf Canyon is then mentioned at the 12m00s mark as an Interactive Information Retrieval Model. The Adaptivity Gain, defined previously as the increase in retrieval performance offered by dynamic ranking over traditional static ranking, calculated from empirical studies done on two collections of TREC queries labeled for multiple intents, is then presented at the 14m10s mark and described as “quite substantial” with NDCG going from 55% to 70%.
“When you think about how much effort search engines are spending to get a 1% improvement in NDCG, this is a lot and could potentially change the upper bound of how good you can get with a single ranking.” – Professor Thorsten Joachims
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.
We 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.
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.
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. surfcanyon.com) and for advertising based on user behavior.
Mark 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:
Surf Canyon develops Dynamic Search, a real-time contextual search technology. By transforming static lists of links into dynamic search pages that automatically and immediately re-order results in response to user behavior signals, searchers are able to more quickly and easily find pertinent information that might otherwise have remained buried as deep as page 100.