An LDAP-based User Modeling Server and its Evaluation

Abstract

Representation components of user modeling servers have been traditionally based on simple file structures and database systems. We propose directory systems as an alternative, which offer numerous advantages over the more traditional approaches: international vendor-independent standardization, demonstrated performance and scalability, dynamic and transparent management of distributed information, built-in replication and synchronization, a rich number of pre-defined types of user information, and extensibility of the core representation language for new information types and for data types with associated semantics. Directories also allow for the virtual centralization of distributed user models and their selective centralized replication if better performance is needed. We present UMS, a user modeling server that is based on the Lightweight Directory Access Protocol (LDAP). UMS allows for the representation of different models (such as user and usage profiles, and system and service models), and for the attachment of arbitrary components that perform user modeling tasks upon these models. External clients such as user-adaptive applications can submit and retrieve information about users. We describe a simulation experiment to test the runtime performance of this server, and present a theory of how the parameters of such an experiment can be derived from empirical web usage research. The results show that the performance of UMS meets the requirements of current small and medium websites already on very modest hardware platforms, and those of very large websites in an entry-level business server configuration.

A Management System for Cyber Individuals and Heterogeneous Data

“…This system is able to act as a centralized user modeling server to support several adaptive Web systems concurrently and offer the user modeling functions, so that Web sites can be automatically adapted to reach the goals of personalization, recommendation, selection, and usage analysis. A. Kobsa also implemented an LDAP based user modeling server (UMS) that allows for the representation of different models [7]. External clients such as user-adaptive applications can submit and retrieve information about users.…”

Performance Evaluation of a Privacy-Enhancing Framework for Personalized Websites

“…A particular product ar- Figure 1 shows an overview of our framework 1 . It consists of external user-adaptive applications, an LDAP-based user modeling server (UMS) [12], a user modeling component (UMC) manager, a Scheduler and a cache database. External user-adaptive applications can retrieve user information from the UMS so as to personalize services to their end users, and can submit additional user information to the UMS.…”

“…1, the cloud denotes the distribution of processing over a network of machines. Distribution of the LDAP-based Directory Component and the UMC Pool have been addressed in [12]. We also distribute the UMC Manager over a network of hosts, each having a stand-alone copy of the UMC Manager.…”

“…Figure 3 depicts the overall testbed architecture. The performance evaluation of the LDAP-based Directory Component and the UMC Pool in [12] had already demonstrated that they scale well and can be deployed to high-workload commercial applications. To be able to measure the performance of the PLA selection and instantiation in isolation, we omitted the Directory Component and created functionless dummy implementations for all UMCs, thereby realistically assuming that those components would run on different hosts anyways when deployed in practice.…”

User data distributed on the social web

“…This is known as "cross-system personalization". Many researches have explored cross-system personalization, focusing on issues such as the communication among distributed systems [2], the heterogeneity management of distributed user and domain data [7,1], the protection of user's privacy during the interoperability process [9] and the identification of the user whose data are exchanged among systems [3,5,13]. This last issue is a starting requirement to enable cross-system personalization since it means, for the different systems partaking into the user data exchange process, to discover if they are referring to the same user.…”