Data display apparatus and data display method

A data display apparatus and data display method for displaying relationships between sets of data are described. Sets of data and similarity values representing similarities between the sets of data are received, and a display is controlled to display representations for the sets of data separated in accordance with the similarity values and so as to display, in a first style, links between representations which correspond to sets of data having a strong similarity value and, in a second style, links between the representations which correspond to sets of data having a weak similarity value

A Prototype “Debugger” for Search Strategies

Knowledge workers such as healthcare information professionals, legal researchers, and librarians need to create and execute search strategies that are effective, efficient and error-free. The traditional solution is to use command-line query builders offered by proprietary database vendors. However, these are based on an archaic approach that offers limited support for the validation and optimisation of their output. Consequently, there are often errors in search strategies reported in the literature that prevent them from being effectively reused or extended. In this paper, we demonstrate a new approach that takes inspiration from software development practice and applies it to the challenge of search strategy formulation. We demonstrate a prototype ‘debugger’ which provides insight into the construction and semantics of search strategies, allowing users to inspect, understand and validate their behaviour and effects. This has the potential to eliminate many sources of error and offers new ways to validate, optimise and re-use search strategies and best practices

Designing the Structured Search Experience: Rethinking the Query-Builder Paradigm

Knowledge workers such as healthcare information professionals, legal researchers, and librarians need to create and execute search strategies that are comprehensive, transparent, and reproducible. The traditional solution is to use command-line query builders offered by proprietary database vendors. However, these are based on a paradigm that dates from the days when users could access databases only via text-based terminals and command-line syntax. In this paper, we present a new approach in which users express concepts as objects on a visual canvas and manipulate them to articulate relationships. This offers a more intuitive user experience (UX) that eliminates many sources of error, makes the query semantics more transparent, and offers new ways to collaborate, share, and optimize search strategies and best practice

Lessons from COVID-19 to Future Evidence Synthesis Efforts: First Living Search Strategy and Out of Date Scientific Publishing and Indexing Industry

Nussbaumer-Streit et al. reported a timely study on the exclusion of non-English language reports in systematic reviews [1] but cautiously generalised the implications to rapid reviews rather than systematic reviews. The results complement the guidance in the new edition of the Cochrane Handbook [2]. However, the time of publication of this report coincides with the COVID-19 outbreak that introduces a geographical bias towards the inclusion of non-English literature. Although many researchers will try to publish in English, literature in non-English should not be ignored. We also thought it will be an added value to share our other experiences on literature search for evidence synthesis on COVID-19

The Information Needs of Mobile Searchers: A Framework

The growing use of Internet-connected mobile devices demands that we reconsider search user interface design in light of the context and information needs specific to mobile users. In this paper the authors present a framework of mobile information needs, juxtaposing search motives—casual, lookup, learn, and investigate—with search types—informational, geographic, personal information management, and transactional

Measures for corpus similarity and homogeneity

How similar are two corpora? A measure of corpus similarity would be very useful for NLP for many purposes, such as estimating the work involved in porting a system from one domain to another. First, we discuss difficulties in identifying what we mean by 'corpus similariti: human similarity judgements are not finegrained enough, corpus similarity is inherently multidimensional, and similarity can only be interpreted in the light of corpus homogeneity. We then present an operational definition of corpus similarity \vhich addresses or circumvents the problems, using purpose-built sets of aknown-similarity corpora". These KSC sets can be used to evaluate the measures. We evaluate the measures described in the literature, including three variants of the information theoretic measure 'perplexity'. A x 2-based measure, using word frequencies, is shnwn to be the best of those tested. The Problem How similar arc two corpora? The question arises on many occasions. In NLP, many useful results can be generated from corpora, but when can the results developed using one corpus be applied to another? How much will it cost to port an NLP application from one domain, with one corpus, to another, with another? For linguistics, does it matter whether language researchers use this corpora or that, or are they similar enough for it to mal<e no difference? There are also questions of more general interest. Looking at British national newspapers: is the Independent more like the Guardian or the Telegraph?' What are the constraints on a measure for corpus similarity? The first is simply that its findings correspond to unequivocal human judgements. It mus

An Internet agent for language model construction

A software agent is described which is able to take a seed (reference) corpus specified by the user, search the Internet for documents which are sufficiently similar to the seed corpus (as defined by a set of similarity metrics operating at a number of levels in the text), and augment the seed corpus with these documents. The size of the corpus and, hopefully, the quality of the derived language model, are thus progressively increased. The seed corpus may be quite a small collection of transcripts from the application domain, such as may be collected with minimal effort. Preliminary results are given for the perplexity of language models constructed using this approach. Potentially, our method has applications well beyond speech recognition, in corpus-based language processing in general, and document retrieval