Capturing Multiple Interests in News Video Retrieval by Incorporating the Ostensive Model

We propose an adaptive news video retrieval approach which is based on the Ostensive Model of developing information needs. We therefore introduce a news video retrieval system called NewsBoy which captures the users’ implicit interactions with its graphical interface, extracts terms from visited video documents and stores them in user profiles. The terms are weighted based on the type of implicit feedback, multiple interests are identified by clustering the content of the profile. In this paper, we describe the architecture of the system and introduce our approach of adding the ostensive factor to capture the users’ evolving interest. Preliminary results show the acceptance of the system and highlights drawbacks.

[1]  John S. Boreczky,et al.  Comparison of video shot boundary detection techniques , 1996, Electronic Imaging.

[2]  Krishna Bharat,et al.  Personalized, interactive news on the Web , 1998, Multimedia Systems.

[3]  Alan F. Smeaton,et al.  User evaluation of Físchlár-News , 2006, ACM Trans. Inf. Syst..

[4]  Wei-Ying Ma,et al.  Multimedia information retrieval: what is it, and why isn't anyone using it? , 2005, MIR '05.

[5]  Carlo Strapparava,et al.  Adaptive Hypermedia and Adaptive Web-Based Systems, 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings , 2008, AH.

[6]  Micheline Hancock-Beaulieu,et al.  An Evaluation of Automatic Query Expansion in an Online Library Catalogue , 1992, J. Documentation.

[7]  David M. Nichols,et al.  Implicit Rating and Filtering , 1998 .

[8]  Iain Campbell,et al.  Supporting Information Needs by Ostensive Definition in an Adaptive Information Space , 1995, MIRO.

[9]  Alan F. Smeaton.  The Físchlár digital library: networked access to a video archive of TV news , 2002 .

[10]  Nicu Sebe,et al.  Personalized multimedia retrieval: the new trend? , 2007, MIR '07.

[11]  Katia P. Sycara,et al.  WebMate: a personal agent for browsing and searching , 1998, AGENTS '98.

[12]  Amanda Spink,et al.  From Highly Relevant to Not Relevant: Examining Different Regions of Relevance , 1998, Inf. Process. Manag..

[13]  Mark Claypool,et al.  Implicit interest indicators , 2001, IUI '01.

[14]  James Allan,et al.  Approaches to passage retrieval in full text information systems , 1993, SIGIR.

[15]  Frank Hopfgartner,et al.  Evaluating the implicit feedback models for adaptive video retrieval , 2007, MIR '07.

[16]  Jaime Teevan,et al.  Implicit feedback for inferring user preference: a bibliography , 2003, SIGF.

[17]  David William Pearson,et al.  Web Information Retrieval Based on User Profile , 2004, AH.

[18]  Stephen E. Robertson,et al.  Okapi at TREC-3 , 1994, TREC.

[19]  Paul Over,et al.  Evaluation campaigns and TRECVid , 2006, MIR '06.

[20]  Stephen E. Robertson,et al.  GatfordCentre for Interactive Systems ResearchDepartment of Information , 1996 .

[21]  Nicholas J. Belkin,et al.  Display time as implicit feedback: understanding task effects , 2004, SIGIR '04.

[22]  Iain Campbell,et al.  The ostensive model of developing information needs , 2000 .

[23]  Derry O'Sullivan,et al.  Explicit vs Implicit Profiling - A Case-Study in Electronic Programme Guides , 2003, IJCAI.