Reference Interview by Jimmy Ghaphery.
More for library students in my topic maps class but others may benefit as well.
The same questions that librarians ask in a “reference interview” are the same sort of questions that will help you identify subjects that should go in a particular topic map.
Your users may not realize there are subjects that will make their finding of other subjects easier in the future. Or that are used by other users in the same department, etc.
The Science and Magic of User and Expert Feedback for Improving Recommendations by Dr. Xavier Amatriain (Telefonica).
Abstract:
Recommender systems are playing a key role in the next web revolution as a practical alternative to traditional search for information access and filtering. Most of these systems use Collaborative Filtering techniques in which predictions are solely based on the feedback of the user and similar peers. Although this approach is considered relatively effective, it has reached some practical limitations such as the so-called Magic Barrier. Many of these limitations strive from the fact that explicit user feedback in the form of ratings is considered the ground truth. However, this feedback has a non-negligible amount of noise and inconsistencies. Furthermore, in most practical applications, we lack enough explicit feedback and would be better off using implicit feedback or usage data.
In the first part of my talk, I will present our studies in analyzing natural noise in explicit feedback and finding ways to overcome it to improve recommendation accuracy. I will also present our study of user implicit feedback and an approach to relate both kinds of information. In the second part, I will introduce a radically different approach to recommendation that is based on the use of the opinions of experts instead of regular peers. I will show how this approach addresses many of the shortcomings of traditional Collaborative Filtering, generates recommendations that are better perceived by the users, and allows for new applications such as fully-privacy preserving recommendations.
Chris Anderson: “We are leaving the age of information and entering the age of recommendation.”
I suspect Chris Anderson must not be an active library user. Long before recommender systems, librarians have been making recommendations to researchers, patrons and children doing homework. I would say we are returning to the age of librarians, assisted by recommender systems.
Librarians use the reference interview so that based on feedback from patrons they can make the appropriate recommendations.
If you substitute librarian for “expert” in this presentation, it becomes apparent the world of information is coming back around to libraries and librarians.
Librarians should be making the case, both in the literature but to researchers like Dr. Amatriain, that librarians can play a vital role in recommender systems.
This is a very enjoyable as well as useful presentation.
For further information see:
It’s All About the Librarian! New Paradigms in Enterprise Discovery and Awareness
This is a must read post by Jeff Jonas.
I won’t spoil your fun but Jeff defines terms such as:
and a number of others.
Looks very much like he is interested in the same issues as topic maps.
Take the time to read it and see what you think.
Exploiting knowledge-in-the-head and knowledge-in-the-social-web: effects of domain expertise on exploratory search in individual and social search environments Authors: Ruogu Kang, Wai-Tat Fu, Thomas George Kannampallil Keywords: domain expertise, exploratory search, search behavior
Abstract:
Our study compared how experts and novices performed exploratory search using a traditional search engine and a social tagging system. As expected, results showed that social tagging systems could facilitate exploratory search for both experts and novices. We, however, also found that experts were better at interpreting the social tags and generating search keywords, which made them better at finding information in both interfaces. Specifically, experts found more general information than novices by better interpretation of social tags in the tagging system; and experts also found more domain-specific information by generating more of their own keywords. We found a dynamic interaction between knowledge-in-the-head and knowledge-in-the-social-web that although information seekers are more and more reliant on information from the social Web, domain expertise is still important in guiding them to find and evaluate the information. Implications on the design of social search systems that facilitate exploratory search are also discussed.
Every librarian should have the first page of this article posted to their office door, every library school on the local bulletin board.
Think about it. Expert searchers (read librarians) find better information than novices and can serve as guides to better information.
More research is needed on how to bridge that gap in search interfaces.
In libraries I think it is now called a “reference interview.”
(Please email, tweet, etc. this post to your librarian friends.)
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