Geyer-Schulz et al. Netscape: my vU File Edit View Go Communicator Help 。3登应 N myvu Favorite Entries Anwendungsprojekt aus Ca :open in new window add to bookmarks others also use experts also use Ziel der Lehrveranstaltung ist die selbstandige Durchfuhrung eines kleinen, aber vollsfindigen EDU-Projekts, wind der Einsatz von Projektmanagementtechniken und softwareengineering Me thoden im Projekt trainiert French Universities open in new window add to bookmarks others also use Diplomanden-und Dissertantenseminar aus Informationswirtschaft open in new window add to bookmarks others also use experts also use rmafionswirts chaft mit besonderer Berucksichtigung der methodischen und nschaftstheoretischen Grundlagen zu usgewahlten actue len Themenbereichen des Faches, Fir Diplomanden und Dissertate Genetische Lemverfahren copen in new window add to bookmarks others also use experts also use RE VIED Lehrziel ist genethsche Lemuertehren(genehische Algonthhen, gene tische Programmierung und classifie Probleme, wie Lagerhaltung, Routenplanung scheduling, Prognoseverfahren, Informaton Retrieval, und fur strategische Entscheidungen einzusetzen. ③回 Fig. 4. Favorite Entries: A my VU-Service expert. Again, this is proportional to the conditional probability P(acec) that an information product ac from category c is purchased, if a user has experience level ec for category (c)For each user, the number of purchases of each information product in the relevant part of his purchase history. This statistic is used for ranking the entries of the Favorite Entries service shown in figure 4 (d) For each user, the number of purchases aggregated for information product categories (e)All products bought at least once by some user (f) From all transactions, an ABC-analysis of information products and cate- gories(for labelling the highest rated group with HOT) 5. As a user requires an information service of my vU, the recommendation agent responsible for this service generates the user interface element which results from this service. We distinguish between "recommender services which im6 Geyer-Schulz et al. Fig. 4. Favorite Entries: A myVU-Service. expert. Again, this is proportional to the conditional probability ✑✓✒✔✚✜✛✝✖ ✢✍✛ ✘ that an information product ✚✣✛ from category ✤ is purchased, if a user has experience level ✢✝✛ for category ✤. (c) For each user, the number of purchases of each information product in the relevant part of his purchase history. This statistic is used for ranking the entries of the Favorite Entries service shown in figure 4. (d) For each user, the number of purchases aggregated for information product categories. (e) All products bought at least once by some user. (f) From all transactions, an ABC-analysis of information products and cate￾gories (for labelling the highest rated group with HOT). 5. As a user requires an information service of myVU, the recommendation agent responsible for this service generates the user interface element which results from this service. We distinguish between “recommender services” which im-