Query Load Balancing by Caching Search Results in Peer-to-Peer Information Retrieval Networks

For peer-to-peer web search engines it is important to keep the delay between receiving a query and providing search results within an acceptable range for the end user. How to achieve this remains an open challenge. One way to reduce delays is by caching search results for queries and allowing peers to access each others cache. In this paper we explore the limitations of search result caching in large-scale peer-to-peer information retrieval networks by simulating such networks with increasing levels of realism. We find that cache hit ratios of at least thirty-three percent are attainable

Recovering Images Based On Their Contents In A Distributed System

The use of peer-to-peer networking as an alternative has become more common in recent years as a means of facilitating the scalable movement of multimedia data. The process of carrying out content-based retrieval in peer-to-peer networks, which are characterized by the distribution of huge quantities of visual data across several nodes, is an important yet challenging topic. In this study, we offer a scalable strategy for content-based picture retrieval in peer-to-peer networks utilizing the bag-of-visual-words paradigm. This is in contrast to most of the previous approaches, which were focused on indexing high-dimensional visual characteristics and had limitations on their scalability. When images are scattered over the whole of the peer-to-peer network, the key challenge lies in efficiently getting a global codebook. This is not a problem in centralized setups because it is easier to access the codebook. A static codebook is less helpful for retrieval tasks in a peer-to-peer network because of the dynamic nature of the growth of the network itself. In order to accomplish this, we present a method for dynamically updating the codebook. This method works by distributing the workload evenly across the nodes that are responsible for handling different code words and optimizing the mutual information that exists between the generated codebook and the relevance information. In order to speed up the retrieval process and cut down on network overhead, researchers are investigating several methods for index trimming. The comprehensive experimental data that we have collected indicates that the method that has been recommended is scalable in dynamic and scattered peer-to-peer networks, all while improving retrieval accuracy

Towards Mapping-Based Document Retrieval in Heterogeneous Digital Libraries

In many scientific domains, researchers depend on a timely and efficient access to available publications in their particular area. The increasing availability of publications in electronic form via digital libraries is a reaction to this need. A remaining problem is the fact that the pool of all available publications is distributed between different libraries. In order to increase the availability of information, these different libraries should be linked in such a way, that all the information is available via any one of them. Peer-to-peer technologies provide sophisticated solutions for this kind of loose integration of information sources. In our work, we consider digital libraries that organize documents according to a dedicated classification hierarchy or provide access to information on the basis of a thesaurus. These kinds of access mechanisms have proven to increase the retrieval result and are therefore widely used. On the other hand, this causes new problems as different sources will use different classifications and thesauri to organize information. This means, that we have to be able to mediate between these different structures. Integrating this mediation into the information retrieval process is a problem that to the best of our knowledge has not been addressed before

From Campus to Community: Making the Case for Open Access by Bringing Nonprofits to Academic Libraries

Summary: Describes how librarians developed a workshop for nonprofit organizations (NPOs) to help NPOs access peer-reviewed publications behind paywalls, develop skills in searching (information retrieval), and improve awareness of how academic libraries can support community organizations. NPOs who participated gave feedback in a number of ways, from written surveys to short recorded video interviews. With permission, their feedback was used to develop promotional and informational materials intended for the campus about the value of open access to those working in the local community

Footprints of information foragers: Behaviour semantics of visual exploration

Social navigation exploits the knowledge and experience of peer users of information resources. A wide variety of visual–spatial approaches become increasingly popular as a means to optimize information access as well as to foster and sustain a virtual community among geographically distributed users. An information landscape is among the most appealing design options of representing and communicating the essence of distributed information resources to users. A fundamental and challenging issue is how an information landscape can be designed such that it will not only preserve the essence of the underlying information structure, but also accommodate the diversity of individual users. The majority of research in social navigation has been focusing on how to extract useful information from what is in common between users' profiles, their interests and preferences. In this article, we explore the role of modelling sequential behaviour patterns of users in augmenting social navigation in thematic landscapes. In particular, we compare and analyse the trails of individual users in thematic spaces along with their cognitive ability measures. We are interested in whether such trails can provide useful guidance for social navigation if they are embedded in a visual–spatial environment. Furthermore, we are interested in whether such information can help users to learn from each other, for example, from the ones who have been successful in retrieving documents. In this article, we first describe how users' trails in sessions of an experimental study of visual information retrieval can be characterized by Hidden Markov Models. Trails of users with the most successful retrieval performance are used to estimate parameters of such models. Optimal virtual trails generated from the models are visualized and animated as if they were actual trails of individual users in order to highlight behavioural patterns that may foster social navigation. The findings of the research will provide direct input to the design of social navigation systems as well as to enrich theories of social navigation in a wider context. These findings will lead to the further development and consolidation of a tightly coupled paradigm of spatial, semantic and social navigation

Cooperative Caching for Multimedia Streaming in Overlay Networks

Traditional data caching, such as web caching, only focuses on how to boost the hit rate of requested objects in caches, and therefore, how to reduce the initial delay for object retrieval. However, for multimedia objects, not only reducing the delay of object retrieval, but also provisioning reasonably stable network bandwidth to clients, while the fetching of the cached objects goes on, is important as well. In this paper, we propose our cooperative caching scheme for a multimedia delivery scenario, supporting a large number of peers over peer-to-peer overlay networks. In order to facilitate multimedia streaming and downloading service from servers, our caching scheme (1) determines the appropriate availability of cached stream segments in a cache community, (2) determines the appropriate peer for cache replacement, and (3) performs bandwidth-aware and availability-aware cache replacement. By doing so, it achieves (1) small delay of stream retrieval, (2) stable bandwidth provisioning during retrieval session, and (3) load balancing of clients' requests among peers

Distributed Information Retrieval using Keyword Auctions

This report motivates the need for large-scale distributed approaches to information retrieval, and proposes solutions based on keyword auctions