{"id":192380,"date":"2015-06-17T00:00:00","date_gmt":"2015-06-17T12:50:56","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/ims-microsoft-research-workshop-foundations-of-data-science-opening-remarks-and-morning-session-i-2\/"},"modified":"2016-07-15T15:24:17","modified_gmt":"2016-07-15T22:24:17","slug":"ims-microsoft-research-workshop-foundations-of-data-science-opening-remarks-and-morning-session-i-2","status":"publish","type":"msr-video","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/video\/ims-microsoft-research-workshop-foundations-of-data-science-opening-remarks-and-morning-session-i-2\/","title":{"rendered":"IMS-Microsoft Research Workshop: Foundations of Data Science – Opening Remarks and Morning Session I"},"content":{"rendered":"
\n

OPENING REMARKS Richard A. Davis<\/p>\n

Susan Dumais Microsoft Research Session Chair Intro: Information Retrieval and Social Media Session<\/p>\n

Cheng Zhai University of Illinois, Urbana Champaign Information Retrieval as Cooperative Game Playing: A Bayesian Decision-Theoretic Framework for Optimizing Intelligent Search Systems<\/p>\n

Search engines play an important role in helping people manage and exploit big text data. The current-generation search engines are fundamentally limited by their narrow definition of the task of information retrieval (IR) as to rank a collection of documents in response to a query. Such a narrow definition does not model accurately the actual retrieval task in a real IR application, where users tend to be engaged in an interactive process with multipe queries, and optimizing the overall performance of an IR system on an entire search session is far more important than its performance on an individual query. In this talk, I will present a new game-theoretic formulation of the IR problem where IR would be regarded as a process of a search engine and a user playing a cooperative game, with a shared goal of satisfying the user’s information need while minimizing the user’s effort and the resource overhead on the retrieval system. I will present a Bayesian decision-theoretic framework for optimizing the actions of such an intelligent interactive search system, where a formal user model would play a central role to tie statistical language modeling, machine learning, and intelligent information retrieval in a unified decision-theoretic framework. The new framework offers two important benefits. First, it naturally suggests optimization of the overall utility of an interactive retrieval system over a whole search session, thus breaking the limitation of the traditional formulation that optimizes ranking of documents for a single query. Second, it models the interactions between users and a search engine, and thus can optimize the collaboration of a search engine and its users, maximizing the “combined intelligence” of a system and users. I will discuss how the new framework not only covers multiple emerging directions in current IR research as special cases, but also opens up many interesting new interdisciplinary research directions in the intersections of information retrieval, machine learning, statistical decision theory, and computational user modeling.<\/p>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

OPENING REMARKS Richard A. Davis Susan Dumais Microsoft Research Session Chair Intro: Information Retrieval and Social Media Session Cheng Zhai University of Illinois, Urbana Champaign Information Retrieval as Cooperative Game Playing: A Bayesian Decision-Theoretic Framework for Optimizing Intelligent Search Systems Search engines play an important role in helping people manage and exploit big text data. […]<\/p>\n","protected":false},"featured_media":199082,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-192380","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/HYb2K-UUKeg","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/192380","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/192380\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media\/199082"}],"wp:attachment":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media?parent=192380"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=192380"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=192380"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=192380"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=192380"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=192380"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=192380"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=192380"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=192380"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=192380"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}