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

An inquiry-based learning approach to teaching information retrieval

The study of information retrieval (IR) has increased in interest and importance with the explosive growth of online information in recent years. Learning about IR within formal courses of study enables users of search engines to use them more knowledgeably and effectively, while providing the starting point for the explorations of new researchers into novel search technologies. Although IR can be taught in a traditional manner of formal classroom instruction with students being led through the details of the subject and expected to reproduce this in assessment, the nature of IR as a topic makes it an ideal subject for inquiry-based learning approaches to teaching. In an inquiry-based learning approach students are introduced to the principles of a subject and then encouraged to develop their understanding by solving structured or open problems. Working through solutions in subsequent class discussions enables students to appreciate the availability of alternative solutions as proposed by their classmates. Following this approach students not only learn the details of IR techniques, but significantly, naturally learn to apply them in solution of problems. In doing this they not only gain an appreciation of alternative solutions to a problem, but also how to assess their relative strengths and weaknesses. Developing confidence and skills in problem solving enables student assessment to be structured around solution of problems. Thus students can be assessed on the basis of their understanding and ability to apply techniques, rather simply their skill at reciting facts. This has the additional benefit of encouraging general problem solving skills which can be of benefit in other subjects. This approach to teaching IR was successfully implemented in an undergraduate module where students were assessed in a written examination exploring their knowledge and understanding of the principles of IR and their ability to apply them to solving problems, and a written assignment based on developing an individual research proposal

Local search: A guide for the information retrieval practitioner

There are a number of combinatorial optimisation problems in information retrieval in which the use of local search methods are worthwhile. The purpose of this paper is to show how local search can be used to solve some well known tasks in information retrieval (IR), how previous research in the field is piecemeal, bereft of a structure and methodologically flawed, and to suggest more rigorous ways of applying local search methods to solve IR problems. We provide a query based taxonomy for analysing the use of local search in IR tasks and an overview of issues such as fitness functions, statistical significance and test collections when conducting experiments on combinatorial optimisation problems. The paper gives a guide on the pitfalls and problems for IR practitioners who wish to use local search to solve their research issues, and gives practical advice on the use of such methods. The query based taxonomy is a novel structure which can be used by the IR practitioner in order to examine the use of local search in IR

Topic based language models for ad hoc information retrieval

We propose a topic based approach lo language modelling for ad-hoc Information Retrieval (IR). Many smoothed estimators used for the multinomial query model in IR rely upon the estimated background collection probabilities. In this paper, we propose a topic based language modelling approach, that uses a more informative prior based on the topical content of a document. In our experiments, the proposed model provides comparable IR performance to the standard models, but when combined in a two stage language model, it outperforms all other estimated models

HILT : High-Level Thesaurus Project. Phase IV and Embedding Project Extension : Final Report

Ensuring that Higher Education (HE) and Further Education (FE) users of the JISC IE can find appropriate learning, research and information resources by subject search and browse in an environment where most national and institutional service providers - usually for very good local reasons - use different subject schemes to describe their resources is a major challenge facing the JISC domain (and, indeed, other domains beyond JISC). Encouraging the use of standard terminologies in some services (institutional repositories, for example) is a related challenge. Under the auspices of the HILT project, JISC has been investigating mechanisms to assist the community with this problem through a JISC Shared Infrastructure Service that would help optimise the value obtained from expenditure on content and services by facilitating subject-search-based resource sharing to benefit users in the learning and research communities. The project has been through a number of phases, with work from earlier phases reported, both in published work elsewhere, and in project reports (see the project website: http://hilt.cdlr.strath.ac.uk/). HILT Phase IV had two elements - the core project, whose focus was 'to research, investigate and develop pilot solutions for problems pertaining to cross-searching multi-subject scheme information environments, as well as providing a variety of other terminological searching aids', and a short extension to encompass the pilot embedding of routines to interact with HILT M2M services in the user interfaces of various information services serving the JISC community. Both elements contributed to the developments summarised in this report

Index ordering by query-independent measures

Conventional approaches to information retrieval search through all applicable entries in an inverted file for a particular collection in order to find those documents with the highest scores. For particularly large collections this may be extremely time consuming. A solution to this problem is to only search a limited amount of the collection at query-time, in order to speed up the retrieval process. In doing this we can also limit the loss in retrieval efficacy (in terms of accuracy of results). The way we achieve this is to firstly identify the most “important” documents within the collection, and sort documents within inverted file lists in order of this “importance”. In this way we limit the amount of information to be searched at query time by eliminating documents of lesser importance, which not only makes the search more efficient, but also limits loss in retrieval accuracy. Our experiments, carried out on the TREC Terabyte collection, report significant savings, in terms of number of postings examined, without significant loss of effectiveness when based on several measures of importance used in isolation, and in combination. Our results point to several ways in which the computation cost of searching large collections of documents can be significantly reduced

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed