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Results
RQ1.1-RQ1.4
Paper B - Peer-to-Peer based Recommendations
for Mobile Commerce
Paper B describes a peer-to-peer based recommender system extension to the
architecture presented in paper A. The basic idea is to provide a distributed
version of collaborative filtering where each peer-to-peer query is a vector with
votes on products and services. This paper tries to answer research question
RQ1.5.
Paper C - Scalable Agent-Based Simulation of Play-
ers in Massively Multiplayer Online Games
Paper C describes an implemented parallel mobile agent platform for the simu-
lation of users (players) in massively multiplayer online games, This platform is
partially based on the architecture described in paper A and B, but this platform
is geared towards one particular service, i.e. massively multiplayer online games.
This paper tries to answer research question RQ2.1.
Paper D - Empirical Performance Evaluation of
the Zereal Massively Multiplayer Online Game
Simulator
Paper D describes empirical scalability testing of the simulation platform pro-
posed in paper C, the method applied is factorial experimental design from statis-
tics. This paper supports paper C in answering research question RQ2.1.
Paper E - Game Usage Mining: Information Gath-
ering for Knowledge Discovery in Massively Mul-
tiplayer Online Games
Paper E presents a taxonomy of computer games from a data mining viewpoint,
a taxonomy of data mining approaches for massively multiplayer online games

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