Query expansion with naive bayes for searching distributed collections

The proliferation of online information resources increases the importance of effective and efficient distributed searching. However, the problem of word mismatch seriously hurts the effectiveness of distributed information retrieval. Automatic query expansion has been suggested as a technique for dealing with the fundamental issue of word mismatch. In this paper, we propose a method - query expansion with Naive Bayes to address the problem, discuss its implementation in IISS system, and present experimental results demonstrating its effectiveness. Such technique not only enhances the discriminatory power of typical queries for choosing the right collections but also hence significantly improves retrieval results

CC-interop : COPAC/Clumps Continuing Technical Cooperation. Final Project Report

As far as is known, CC-interop was the first project of its kind anywhere in the world and still is. Its basic aim was to test the feasibility of cross-searching between physical and virtual union catalogues, using COPAC and the three functioning "clumps" or virtual union catalogues (CAIRNS, InforM25, and RIDING), all funded or part-funded by JISC in recent years. The key issues investigated were technical interoperability of catalogues, use of collection level descriptions to search union catalogues dynamically, quality of standards in cataloguing and indexing practices, and usability of union catalogues for real users. The conclusions of the project were expected to, and indeed do, contribute to the development of the JISC Information Environment and to the ongoing debate as to the feasibility and desirability of creating a national UK catalogue. They also inhabit the territory of collection level descriptions (CLDs) and the wider services of JISC's Information Environment Services Registry (IESR). The results of this project will also have applicability for the common information environment, particularly through the landscaping work done via SCONE/CAIRNS. This work is relevant not just to HE and not just to digital materials, but encompasses other sectors and domains and caters for print resources as well. Key findings are thematically grouped as follows: System performance when inter-linking COPAC and the Z39.50 clumps. The various individual Z39.50 configurations permit technical interoperability relatively easily but only limited semantic interoperability is possible. Disparate cataloguing and indexing practices are an impairment to semantic interoperability, not just for catalogues but also for CLDs and descriptions of services (like those constituting JISC's IESR). Creating dynamic landscaping through CLDs: routines can be written to allow collection description databases to be output in formats that other UK users of CLDs, including developers of the JISC information environment. Searching a distributed (virtual) catalogue or clump via Z39.50: use of Z39.50 to Z39.50 middleware permits a distributed catalogue to be searched via Z39.50 from such disparate user services as another virtual union catalogue or clump, a physical union catalogue like COPAC, an individual Z client and other IE services. The breakthrough in this Z39.50 to Z39.50 conundrum came with the discovery that the JISC-funded JAFER software (a result of the 5/99 programme) meets many of the requirements and can be used by the current clumps services. It is technically possible for the user to select all or a sub-set of available end destination Z39.50 servers (we call this "landscaping") within this middleware. Comparing results processing between COPAC and clumps. Most distributed services (clumps) do not bring back complete results sets from associated Z servers (in order to save time for users). COPAC on-the-fly routines could feasibly be applied to the clumps services. An automated search set up to repeat its query of 17 catalogues in a clump (InforM25) hourly over nearly 3 months returned surprisingly good results; for example, over 90% of responses were received in less than one second, and no servers showed slower response times in periods of traditionally heavy OPAC use (mid-morning to early evening). User behaviour when cross-searching catalogues: the importance to users of a number of on-screen features, including the ability to refine a search and clear indication that a search is processing. The importance to users of information about the availability of an item as well as the holdings data. The impact of search tools such as Google and Amazon on user behaviour and the expectations of more information than is normally available from a library catalogue. The distrust of some librarians interviewed of the data sources in virtual union catalogues, thinking that there was not true interoperability

Peer to Peer Information Retrieval: An Overview

Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom

Optimal Information Retrieval with Complex Utility Functions

Existing retrieval models all attempt to optimize one single utility function, which is often based on the topical relevance of a document with respect to a query. In real applications, retrieval involves more complex utility functions that may involve preferences on several different dimensions. In this paper, we present a general optimization framework for retrieval with complex utility functions. A query language is designed according to this framework to enable users to submit complex queries. We propose an efficient algorithm for retrieval with complex utility functions based on the a-priori algorithm. As a case study, we apply our algorithm to a complex utility retrieval problem in distributed IR. Experiment results show that our algorithm allows for flexible tradeoff between multiple retrieval criteria. Finally, we study the efficiency issue of our algorithm on simulated data

SPEIR: Scottish Portals for Education, Information and Research. Final Project Report: Elements and Future Development Requirements of a Common Information Environment for Scotland

The SPEIR (Scottish Portals for Education, Information and Research) project was funded by the Scottish Library and Information Council (SLIC). It ran from February 2003 to September 2004, slightly longer than the 18 months originally scheduled and was managed by the Centre for Digital Library Research (CDLR). With SLIC's agreement, community stakeholders were represented in the project by the Confederation of Scottish Mini-Cooperatives (CoSMiC), an organisation whose members include SLIC, the National Library of Scotland (NLS), the Scottish Further Education Unit (SFEU), the Scottish Confederation of University and Research Libraries (SCURL), regional cooperatives such as the Ayrshire Libraries Forum (ALF)1, and representatives from the Museums and Archives communities in Scotland. Aims; A Common Information Environment For Scotland The aims of the project were to: o Conduct basic research into the distributed information infrastructure requirements of the Scottish Cultural Portal pilot and the public library CAIRNS integration proposal; o Develop associated pilot facilities by enhancing existing facilities or developing new ones; o Ensure that both infrastructure proposals and pilot facilities were sufficiently generic to be utilised in support of other portals developed by the Scottish information community; o Ensure the interoperability of infrastructural elements beyond Scotland through adherence to established or developing national and international standards. Since the Scottish information landscape is taken by CoSMiC members to encompass relevant activities in Archives, Libraries, Museums, and related domains, the project was, in essence, concerned with identifying, researching, and developing the elements of an internationally interoperable common information environment for Scotland, and of determining the best path for future progress

Investigating the feasibility of a distributed, mapping-based, approach to solving subject interoperability problems in a multi-scheme, cross-service, retrieval environment

The HILT project is researching the problems of facilitating interoperability of subject descriptions in a distributed multi-scheme environment. HILT Phase I found a UK community consensus in favour of utilising an inter-scheme mapping service to improve interoperability. HILT Phase II investigated the approach by building a pilot server, and identified a range of issues that would have to be tackled if an operational service was to be successful. HILT Phase III will implement a centralised version of an M2M pilot, but will aim to design it so that the possibility of a move to a distributed service remains open. This aim will impact on likely future research concerns in Phase III and beyond. Wide adoption of a distributed approach to the problem could lead to the creation of a framework within which regional, national, and international efforts in the area can be harmonised and co-ordinated

Efficient Subgraph Matching on Billion Node Graphs

The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query processing. Typically, most indices require either super-linear indexing time or super-linear indexing space. Unfortunately, for very large graphs, super-linear approaches are almost always infeasible. In this paper, we study the problem of subgraph matching on billion-node graphs. We present a novel algorithm that supports efficient subgraph matching for graphs deployed on a distributed memory store. Instead of relying on super-linear indices, we use efficient graph exploration and massive parallel computing for query processing. Our experimental results demonstrate the feasibility of performing subgraph matching on web-scale graph data.Comment: VLDB201