Saracevic on Relevance and Interaction

There is no Nobel Prize in computer science, despite computer science having done more than any other discipline in the past fifty years to change the world. Instead, there is the Turing Award, which serves as a Nobel Prize of computing.

But the Turing Award has never been given to anyone in information retrieval. Instead, there is the Gerard Salton Award, which serves as a Turing Award of information retrieval. Its recipients represent an A-list of information retrieval researchers.

Last week, I had the opportunity to talk with Salton Award recipient Tefko Saracevic. If you are not familiar with Saracevic, I suggest you take an hour to watch his 2007 lecture on “Relevance in information science”.

I won’t try to capture an hour of conversation in a blog post, but here are a few highlights:

  • We learn from philosophers, particularly Alfred Schütz, that we cannot reduce relevance to a single concept, but rather have to consider a system of interdependent relevancies, such as topical relevance, interpretational relevance, and motivational relevance.
  • When we talk about relevance measures, such as precision and recall, we evaluate results from the perspective of a user. But information retrieval approaches necessarily take a systems perspective, making assumptions about what people will want and encoding those assumptions in models and algorithms.
  • A major challenge in the information retrieval is that users–particularly web search users–often formulate queries that are ineffective, particularly because they are too short. Studies have shown that reference interviews can lead to improved retrieval effectiveness (typically through longer, more informative queries). He said that automated systems could help too, but he wasn’t aware of any that had achieved traction.
  • A variety of factors affect interactive information retrieval, including task context, intent, expertise. Moreover, people react to certain relevance clues more than others, and more within some populations than others.

As I expected, I walked away with more questions than answers. But I did walk away reassured that my colleagues and I at Endeca , along with others in the HCIR community, are attacking the right problem: helping users formulate better queries.

I’d like to close with an anecdote that Saracevic recounts in his 2007 lecture. Bruce Croft had just delivered an information retrieval talk, and Nick Belkin raised the objection that users need to be incorporated into the study. Croft’s conversation-ending response: “Tell us what to do, and we will do it.”

We’re halfway there. We’ve built interactive information retrieval systems, and we see from deployment after deployment that they work. Not that there isn’t plenty of room for improvement, but the unmet challenge, as Ellen Voorhees makes clear, is evaluation. We need to address Nick Belkin’s grand challenge and establish a paradigm suitable for evaluation of interactive IR systems.

By Daniel Tunkelang

High-Class Consultant.

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