We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    Flat editorial illustration: The article connects AI and marketing analytics with managerial judgment grounded in consumer behavi
    How an Online MBA in Marketing Connects AI and Data Analytics
    11 Min Read
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Search User Interfaces and Data Quality
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Search User Interfaces and Data Quality
Uncategorized

Search User Interfaces and Data Quality

Daniel Tunkelang
Daniel Tunkelang
6 Min Read
Search User Interfaces and Data Quality
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

One of the many things I’ve enjoyed in my first few weeks of working at Google is the opportunity to talk with many people who care about user interfaces and think about HCIR. Indeed, some of the folks working on “more and better search refinements” are just steps away from my desk. Very cool!

But working on the inside has also help me appreciate what Bob Wyman tried to tell me months ago – that Google has no philosophical predilection towards black box approaches, but rather is only limited by what technology makes possible and what its engineers can implement. I’d qualify that slightly by saying that I perceive an additional constraint: Google does have a strong predilection towards data-driven decisions. Some folks have found that approach objectionable in the context of interface design.

Anyway, if you’re a regular here, then you’re probably predisposed towards HCIR and exploratory search. In that case, I’d like to take a moment to help you appreciate the challenge I face on a day-to-day basis.

More Read

How to Unlock the Value of Your Data in Real-Time
How to Unlock the Value of Your Data in Real-Time
Permission Marketing
Do You Need a Data Scientist or a Marketing Researcher?
Creating a Culture of Transparency
Social Media Marketers Should Get Ahead of the Curve

Which one of these two statements do you most agree with?

  1. We need better data quality in order to support richer search user interfaces.
  2. Richer search user interfaces allow us to overcome data quality limitations.

On one hand, consider two search engines whose interfaces are designed to support exploratory search: Cuil and Kosmix. Sometimes they’re great, e.g., [michael jackson] on Cuil and [iraq] on Kosmix. But look what can happen for queries that are further out in the tail, e.g. [faceted search] on Cuil [real time search] on Kosmix. Yes, the kinds of queries I make. I don’t mean to knock these guys – they’re trying, and their efforts are admirable. Moreover, both generally return respectable search results on the first pages (in Kosmix’s case, through federation). But the search refinements can be way off, and that undermine the overall experience. I strongly suspect that the problem is one of data quality, along the lines of what others have argued.

On the other hand, some of the work that I did with colleagues at Endeca (e.g., work presented at HCIR 2008 on “Supporting Exploratory Search for the ACM Digital Library”) at least dangles the possibility that the second statement holds – namely, a richer user interface could help overcome data quality limitations. Interaction draws more of the information need out of the user, and the process may be able to mask imperfection in the data. For example, it’s clear to users – and clear from the search refinements – that [michael jackson beer] and [michael jackson -beer] are about different people. If we can just get that incremental information from the user, we don’t have to achieve perfection in named entity recognition and disambiguation.

I think there’s some truth in both arguments. Data quality is a major bottleneck for effectively delivering an exploratory search experience, and data quantity, much as it helps, is not a guarantee of quality. Richer interfaces offer the enticing possibility of leveraging human computation, but they also introduce the risk of disappointing and alienating users. Even for an HCIR zealot like me, the constraints of reality are sobering.

And yes, speed and computational cost matter too. But hey, it wouldn’t be a grand challenge if it were easy!

Link to original post

TAGGED:data qualityexploratory search
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: A technology-editorial comparison of disconnected origination, servicing, and collections records dr
The Data Reconciliation Problem Inside Disconnected Lending Systems
Big Data Exclusive Fintech
Flat editorial illustration: The article connects AI and marketing analytics with managerial judgment grounded in consumer behavi
How an Online MBA in Marketing Connects AI and Data Analytics
Analytics Artificial Intelligence Big Data Exclusive
Flat editorial illustration: The article connects commercial drone capture with integrated software workflows that organize and r
Drone Technology as a Business Investment: Calculating ROI, Costs, and Long-Term Value
Business Intelligence Marketing Software
Flat editorial illustration: The article connects weekly technician productivity and related shop metrics to timely scheduling an
Workforce Analytics for Auto Repair Shops: Reading Technician Productivity Weekly
Business Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Data Quality: A Cause and Effect Story
Business IntelligencePredictive Analytics

Data Quality: A Cause and Effect Story

4 Min Read
Commendable Comments (Part 1)
Uncategorized

Commendable Comments (Part 1)

13 Min Read
Maybe you're just not that into your data?
Uncategorized

Maybe you’re just not that into your data?

8 Min Read
Data Quality – Everyone is a Stakeholder
Data QualityPolicy and Governance

Data Quality – Everyone is a Stakeholder

7 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

From Bolts to Bots: How AI Is Fortifying the Automotive Industry
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?