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Beyond Information Retrieval: When and how not to find things| old_uid | 10001 |
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| title | Beyond Information Retrieval: When and how not to find things |
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| start_date | 2015/09/17 |
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| schedule | 15h |
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| online | no |
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| location_info | salle 24-25/405 |
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| details | Séminaire MLIA sur la thématique de la recherche d'information |
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| summary | The traditional role of a search engine is much like the traditional role of a library: generally the objective is to help people find things. As we get better at this, however, we have been encountering an increasing number of cases in which some things that we know exist simply should not be found. Some well known examples include removal of improperly posted copyrighted material from search engine indexes, and the evolving legal doctrine that is now commonly referred to as the “right to be forgotten.” Some such cases are simple, relying on users to detect specific content that should be flushed from a specific index. Other cases, however, are more complex. For example, in the aspect of the civil litigation process known as e-discovery, one side may be entitled to withhold entire classes of material that may not have been labeled in advance (bcause of attorney-client privilege). An even more complex example is government transparency, in which for public policy reasons we may want to make some information public, despite that information being intermixed with other information that must be protected. Professional archivists have long dealt with such challenges, so perhaps we should start thinking about how to build search engines that act less like a library and more like an archive. In this talk, I will use these and other examples to introduce the idea of “search among secrets” in which the goal is to help some users find some content while protecting some content from some users (or some uses). We’ll dive down to look at how this actually works today in a few specific cases, with particular attention to how queries are formulated and which parts of the process are, or might be, automated. With that as background, I will then offer a few initial thoughts on how we might evaluate such systems. I’ll conclude with an invitation to think together about how information retrieval researchers might, together with others, begin to tackle these challenges.
About the Speaker:
Douglas Oard is a Professor at the University of Maryland, College Park, with joint appointments in the College of Information Studies (Maryland’s iSchool) and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Dr. Oard earned his Ph.D. in Electrical Engineering from the University of Maryland. His research interests center around the use of emerging technologies to support information seeking by end users. |
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| responsibles | <not specified> |
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