01582nas a2200241   4500008004100000245008200041210006900123260000900192300001200201490000600213520077800219653004100997653002401038653002301062653002301085653001601108653002601124100001801150700001701168700002101185700001701206856011701223       2010                        eng d00aHierarchical clustering in medical document collections: The BIC-means method0 aHierarchical clustering in medical document collections The BICm  c2010  a71 - 770 v83 aHierarchical clustering of text collections is a key problem in document management and retrieval. In partitional hierarchical clustering, which is more efficient than its agglomerative counterpart, the entire collection is split into clusters and the individual clusters are further split until a heuristicallymotivated termination criterion is met. In this paper, we define the BIC-means algorithm, which applies the Bayesian Information Criterion (BIC) as a domain independent termination criterion for partitional hierarchical clustering. We evaluate the effectiveness of BIC-means in clustering and retrieval on medical document collections and we propose a dynamic version of the BIC-Means algorithm for adapting an existing clustering solution to document additions.10aBayesian information criterion (BIC)10aDocument clustering10aDocument retrieval10aDynamic clustering10aPerformance10aTermination criterion1 aHourdakis, N.1 aArgyriou, M.1 aPetrakis, E.G.M.1 aMilios, E.E.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960667355&partnerID=40&md5=87c5599ab55c27b1d1ae1f1f2e76cd6b02193nas a2200205   4500008004100000245010100041210006900142260000900211300001400220490000600234520145900240653004101699653002401740653002301764653002301787653001601810653002601826100001801852856011701870       2010                        eng d00aA specification model for temporal and spatial relations of segments in multimedia presentations0 aspecification model for temporal and spatial relations of segmen  c2010  a136 - 1460 v83 aIn this paper, we introduce a conceptual tuplebased model for specification of spatial, temporal and semantic relationships among media segments in a multimedia presentation. A multimedia presentation contains various kinds of multimedia objects such as audio, video, images, text media types and so on. The organization of a presentation is a complex task in that the display order of presentation content (in time and space) must be specified. The critical decisions for presentation construction include content selection, content organization, and content delivery. Once the decision is made on the organization of the content of the presentation, it must be conveyed to the end user in the correct organizational order and in a timely fashion. Assuming that a set of multimedia segments gets organized into a presentation graph, this conceptual model formalizes a complete presentation using event-points for these segments. Three possible end-user environments of multimedia presentation are considered for presentation playout as (i) the one without any constraint, (ii) another one with a single constraint, and (iii) the third one with multiple constraints (one constraint for each type of multimedia segments in the organized presentation). In accordance with these limitations (i.e., without violating any of the end-user specified constraints), we give three methods for constructed presentations to be presented at the presentation terminal.10aBayesian information criterion (BIC)10aDocument clustering10aDocument retrieval10aDynamic clustering10aPerformance10aTermination criterion1 aHakkoymaz, V.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960249136&partnerID=40&md5=da73c8932dcd46bf41b98910c87b5916