Software agents interact to solve tasks, the details of which need to be described in a language understandable by all the actors involved. Ontologies provide a formalism for defining both the domain of the task and the terminology used to describe it. However, finding a shared ontology has proved difficult: different institutions and developers have different needs and formalise them in different ontologies. In a closed environment it is possible to force all the participants to share the same ontology, while in open and distributed environments ontology mapping can provide interoperability between heterogeneous interacting actors. However, conventional mapping systems focus on acquiring static information, and on mapping whole ontologies, which is infeasible in open systems. This thesis shows a different approach to the problem of heterogeneity. It starts from the intuitive idea that when similar situations arise, similar interactions are performed. If the interactions between actors are specified in formal scripts, shared by all the participants, then when the same situation arises, the same script is used. The main hypothesis that this thesis aims to demonstrate is that by analysing different runs of these scripts it is possible to create a statistical model of the interactions, that reflect the frequency of terms in messages and of ontological relations between terms in different messages. The model is then used during a run of a known interaction to compute the probability distribution for terms in received messages. The probability distribution provides additional information, contextual to the interaction, that can be used by a traditional ontology matcher in order to improve efficiency, by reducing the comparisons to the most likely ones given the context, and possibly both recall and precision, in particular helping disambiguation. The ability to create a model that reflects real phenomena in this sort of environment is evaluated by analysing the quality of the predictions, in particular verifying how various features of the interactions, such as their non-stationarity, affect the predictions. The actual improvements to a matcher we developed are also evaluated. The overall results are very promising, as using the predictor can lower the overall computation time for matching by ten times, while maintaining or in some cases improving recall and precision.

The proliferation of online communities on the Internet nowadays may lead people to the conclusion that the development of custom-made communities for particular purpose is straightforward. Unfortunately, this is not the case. Although software providing basic community infrastructure is readily available, it is not enough to ensure that the online community will take off and become sustained. Most online communities suffer from the scarcity of the user participation in their initial phase. To address the problem, this thesis proposes a motivational mechanism to encourage user participation. The main idea is to introduce a set of hierarchical memberships into online communities and reward active users with better quality of services. The mechanism has been applied in a small-scale online community called Comtella and evaluated. The results showed that, although the mechanism was able to motivate users to participate more actively and make more contributions, it led to a deteriorating quality of user contributions, catalyzed information overload in the community and resulted in a decrease in user participation towards the end of the study. <p> Therefore, to regulate the quality and the quantity of user contributions and ensure a sustainable level of user participation in the online community, the proposed mechanism was improved so that it was able to adapt the rewards for particular forms of participation for individual users depending on their reputation and the current need of the community, thereby influencing their actions of contributing. The improved mechanism was also implemented and evaluated in the Comtella system. The results of evaluation showed that the mechanism can guarantee stable and active user participation and lower the level of information overload in the online community and therefore it can enhance the sustainability of the community.

The proliferation of online communities on the Internet nowadays may lead people to the conclusion that the development of custom-made communities for particular purpose is straightforward. Unfortunately, this is not the case. Although software providing basic community infrastructure is readily available, it is not enough to ensure that the online community will take off and become sustained. Most online communities suffer from the scarcity of the user participation in their initial phase. To address the problem, this thesis proposes a motivational mechanism to encourage user participation. The main idea is to introduce a set of hierarchical memberships into online communities and reward active users with better quality of services. The mechanism has been applied in a small-scale online community called Comtella and evaluated. The results showed that, although the mechanism was able to motivate users to participate more actively and make more contributions, it led to a deteriorating quality of user contributions, catalyzed information overload in the community and resulted in a decrease in user participation towards the end of the study. <p> Therefore, to regulate the quality and the quantity of user contributions and ensure a sustainable level of user participation in the online community, the proposed mechanism was improved so that it was able to adapt the rewards for particular forms of participation for individual users depending on their reputation and the current need of the community, thereby influencing their actions of contributing. The improved mechanism was also implemented and evaluated in the Comtella system. The results of evaluation showed that the mechanism can guarantee stable and active user participation and lower the level of information overload in the online community and therefore it can enhance the sustainability of the community.

We propose a balanced tree structure overlay on a peer-to-peer network capable of supporting both exact queries and range queries efficiently. In spite of the tree structure causing distinctions to be made between nodes at different levels in the tree, we show that the load at each node is approximately equal. In spite of the tree structure providing precisely one path between any pair of nodes, we show that sideways routing tables maintained at each node provide sufficient fault tolerance to permit efficient repair. Specifically, in a network with N nodes, we guarantee that both exact queries and range queries can be answered in O(logN) steps and also that update operations (to both data and network) have an amortized cost of O(logN). An experimental assessment validates the practicality of our proposal. / Singapore-MIT Alliance (SMA)

The Internet-of-Things is an open source architecture for enabling information sharing between globally connected devices, which existing system do not offer. However, the Internet-of-Things induces the single points of failure and long communication delay. Thus, the Sensible Things platform is proposed, which is a fully distributed system. So far, it has produced components to share sensor and actuator information on the Internet. In the past, manual work was problematic since physical access could be difficult on remote locations. There were also difficulties to detect if the devices were actually working properly. Therefore, the thesis mainly focuses on the functionality which is able to check status, update software automatically and restart the devices with new software. The thesis first analyzes the mechanism of the automatic updating and describes the methods for it. The automatic updates of demonstrator is implemented in My-Eclipse. Finally, this paper describes the evaluation of the automatic updating in Sensible Things platform.

Peer to peer systems have been widely used in the internet. However, most of the peer to peer information systems are still missing some of the important features, for example cross-language IR (Information Retrieval) and collection selection / fusion features. Cross-language IR is the state-of-art research area in IR research community. It has not been used in any real world IR systems yet. Cross-language IR has the ability to issue a query in one language and receive documents in other languages. In typical peer to peer environment, users are from multiple countries. Their collections are definitely in multiple languages. Cross-language IR can help users to find documents more easily. E.g. many Chinese researchers will search research papers in both Chinese and English. With Cross-language IR, they can do one query in Chinese and get documents in two languages. The Out Of Vocabulary (OOV) problem is one of the key research areas in crosslanguage information retrieval. In recent years, web mining was shown to be one of the effective approaches to solving this problem. However, how to extract Multiword Lexical Units (MLUs) from the web content and how to select the correct translations from the extracted candidate MLUs are still two difficult problems in web mining based automated translation approaches. Discovering resource descriptions and merging results obtained from remote search engines are two key issues in distributed information retrieval studies. In uncooperative environments, query-based sampling and normalized-score based merging strategies are well-known approaches to solve such problems. However, such approaches only consider the content of the remote database but do not consider the retrieval performance of the remote search engine. This thesis presents research on building a peer to peer IR system with crosslanguage IR and advance collection profiling technique for fusion features. Particularly, this thesis first presents a new Chinese term measurement and new Chinese MLU extraction process that works well on small corpora. An approach to selection of MLUs in a more accurate manner is also presented. After that, this thesis proposes a collection profiling strategy which can discover not only collection content but also retrieval performance of the remote search engine. Based on collection profiling, a web-based query classification method and two collection fusion approaches are developed and presented in this thesis. Our experiments show that the proposed strategies are effective in merging results in uncooperative peer to peer environments. Here, an uncooperative environment is defined as each peer in the system is autonomous. Peer like to share documents but they do not share collection statistics. This environment is a typical peer to peer IR environment. Finally, all those approaches are grouped together to build up a secure peer to peer multilingual IR system that cooperates through X.509 and email system.

Im Rahmen der Dissertation wurde ein Middlewaredienst entwickelt und realisiert. Es gestattet die dynamische Verwaltung heterogener Kontextquellen. Das zugrunde liegende Komponentenmodell selbstbeschreibender Context Provieder ermöglicht die lose Kopplung von Kontextquellen und -senken. Es wird durch Filter- und Konverterkomponenten zur generischen Providersselektion anhand domänenspezifischer Merkmale ergänzt. Die Kopplung der verteilten Dienstinstanzen erfolgt durch ein hybrides Peer-to-Peer-System. Dies trägt der Heterogenität der Endgeräte Rechnung, und erlaubt die skalierbare , verteilte Verwaltung von Kontextquellen in globalen Szenarien.

Im Rahmen der Dissertation wurde ein Middlewaredienst entwickelt und realisiert. Es gestattet die dynamische Verwaltung heterogener Kontextquellen. Das zugrunde liegende Komponentenmodell selbstbeschreibender Context Provieder ermöglicht die lose Kopplung von Kontextquellen und -senken. Es wird durch Filter- und Konverterkomponenten zur generischen Providersselektion anhand domänenspezifischer Merkmale ergänzt. Die Kopplung der verteilten Dienstinstanzen erfolgt durch ein hybrides Peer-to-Peer-System. Dies trägt der Heterogenität der Endgeräte Rechnung, und erlaubt die skalierbare , verteilte Verwaltung von Kontextquellen in globalen Szenarien.