Exploring Explortatory Search

November 18, 2009
48 Views

Google’s recently released Image Swirl is slick. But I’ve been struggling to figure out whether it’s useful or simply a showcase for cool technology.

And that’s prompted me to think about the overloaded term “exploratory search.” A while back, I tried to define exploratory search based on what it is not. This time, let me aim to positively characterize what I see as its two primary use cases:

  1. I know what I want, but I don’t know how to describe it.
  2. I don’t know what I want, but I hope to figure it out once I see what’s out there.

The first use case cries out for tools that support query refinement or elaboration. Existing tools span a range from suggesting spelling corrections (aka “did you mean”) to offering semantically or statistically related searches that hopefully provide the user with at least a step in the right direction. One of my favorite approaches, faceted search, is primarily used to support query refinement through progressive narrowing of an initial search query.

The second “I don’t know what I want” use case is fuzzier. In the language of machine learning, this use case is unsupervised, while the previous one is supervised. In general, it’s a lot

Google’s recently released Image Swirl is slick. But I’ve been struggling to figure out whether it’s useful or simply a showcase for cool technology.

And that’s prompted me to think about the overloaded term “exploratory search.” A while back, I tried to define exploratory search based on what it is not. This time, let me aim to positively characterize what I see as its two primary use cases:

  1. I know what I want, but I don’t know how to describe it.
  2. I don’t know what I want, but I hope to figure it out once I see what’s out there.

The first use case cries out for tools that support query refinement or elaboration. Existing tools span a range from suggesting spelling corrections (aka “did you mean”) to offering semantically or statistically related searches that hopefully provide the user with at least a step in the right direction. One of my favorite approaches, faceted search, is primarily used to support query refinement through progressive narrowing of an initial search query.

The second “I don’t know what I want” use case is fuzzier. In the language of machine learning, this use case is unsupervised, while the previous one is supervised. In general, it’s a lot harder to define or evaluate outcomes for unsupervised scenarios. Indeed, Hal Daume has argued that we should only do unsupervised learning if we do not have a trustworthy automatic evaluation metric. That’s a strong position, and you can see some of the counterarguments in his comment thread. But, going back to our scenario, it’s really hard to judge the effectiveness of tools like similarity browsing when they support exploration in the absence of any concrete goal.

With that in mind, I’ll reserve judgment on the utility of tools like Image Swirl. To the extent that it aims at the first use case, clustering images for a particular search, I’m ambivalent. I’d prefer a more transparent interface, in which I have more of a sense of control over the navigational experience. I suspect it is more aimed at the second use case, offering a compact visualization of what is out there.

Besides, as some folks have brought up at the HCIR workshops, it’s important that we make information seeking fun. And Swirl certainly scores on that front.

Link to original post

You may be interested

How SAP Hana is Driving Big Data Startups
Big Data
298 shares3,130 views
Big Data
298 shares3,130 views

How SAP Hana is Driving Big Data Startups

Ryan Kh - July 20, 2017

The first version of SAP Hana was released in 2010, before Hadoop and other big data extraction tools were introduced.…

Data Erasing Software vs Physical Destruction: Sustainable Way of Data Deletion
Data Management
78 views
Data Management
78 views

Data Erasing Software vs Physical Destruction: Sustainable Way of Data Deletion

Manish Bhickta - July 20, 2017

Physical Data destruction techniques are efficient enough to destroy data, but they can never be considered eco-friendly. On the other…

10 Simple Rules for Creating a Good Data Management Plan
Data Management
69 shares688 views
Data Management
69 shares688 views

10 Simple Rules for Creating a Good Data Management Plan

GloriaKopp - July 20, 2017

Part of business planning is arranging how data will be used in the development of a project. This is why…