000178472 001__ 178472
000178472 005__ 20180913061340.0
000178472 02470 $$2ISI$$a000298962502140
000178472 037__ $$aCONF
000178472 245__ $$aBrowsing Catalogue Graphs: Content Caching Supercharged!!
000178472 269__ $$a2011
000178472 260__ $$bIeee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa$$c2011
000178472 336__ $$aConference Papers
000178472 490__ $$aIEEE International Conference on Image Processing ICIP
000178472 520__ $$aWe consider a generic scenario of content browsing where a client is presented with a catalogue of items of interest. Upon the selection of an item from a page of the catalogue, the client can choose the next item to browse from a list of related items presented on the same page. The system has limited resources to have all items available for immediate access by the browsing client. Therefore, it pays a penalty when the client selects an unavailable item. Conversely, there is a reward that the system gains when the client selects an immediately available item. We formulate the optimization problem of selecting the subset of items that the system should have for immediate access such that its profit is maximized, for the given system resources. We design two techniques for solving the optimization problem in linear time, as a function of the catalogue size. We examine their performance via numerical simulations that reveal their core properties. We also study their operation on actual YouTube data and compare their efficiency relative to conventional solutions. Substantial performance gains are demonstrated, due to accounting for the content graph imposed by the catalogue of items.
000178472 700__ $$aChakareski, Jacob
000178472 7112_ $$aIEEE International Conference On Image Processing (ICIP)$$cBrussels, BELGIUM$$dSep 11-14, 2011
000178472 773__ $$q-$$tIEEE International Conference On Image Processing (ICIP)
000178472 909C0 $$0252393$$pLTS4$$xU10851
000178472 909CO $$ooai:infoscience.tind.io:178472$$pconf$$pSTI
000178472 917Z8 $$x101475
000178472 937__ $$aEPFL-CONF-178472
000178472 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000178472 980__ $$aCONF