Search (29 results, page 1 of 2)

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Abstract

We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.

Source

Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al

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Abstract

Information searching in practice seldom is an end in itself. In work, work task (WT) performance forms the context, which information searching should serve. Therefore, information retrieval (IR) systems development/evaluation should take the WT context into account. The present paper analyzes how WT features: task complexity and task types, affect information searching in authentic work: the types of information needs, search processes, and search media. We collected data on 22 information professionals in authentic work situations in three organization types: city administration, universities, and companies. The data comprise 286 WTs and 420 search tasks (STs). The data include transaction logs, video recordings, daily questionnaires, interviews. and observation. The data were analyzed quantitatively. Even if the participants used a range of search media, most STs were simple throughout the data, and up to 42% of WTs did not include searching. WT's effects on STs are not straightforward: different WT types react differently to WT complexity. Due to the simplicity of authentic searching, the WT/ST types in interactive IR experiments should be reconsidered.

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Abstract

The paper reports a longitudinal analysis of the topical and methodological development of Library and Information Science (LIS). Its focus is on the effects of researchers' disciplines on these developments. The study extends an earlier cross-sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706-1722) by a coordinated dataset representing a content analysis of articles published in 31 scholarly LIS journals in 1995, 2005, and 2015. It is novel in its coverage of authors' disciplines, topical and methodological aspects in a coordinated dataset spanning two decades thus allowing trend analysis. The findings include a shrinking trend in the share of LIS from 67 to 36% while Computer Science, and Business and Economics increase their share from 9 and 6% to 21 and 16%, respectively. The earlier cross-sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706-1722) for the year 2015 identified three topical clusters of LIS research, focusing on topical subfields, methodologies, and contributing disciplines. Correspondence analysis confirms their existence already in 1995 and traces their development through the decades. The contributing disciplines infuse their concepts, research questions, and approaches to LIS and may also subsume vital parts of LIS in their own structures of knowledge production.

Date

22. 6.2023 18:15:06

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Abstract

Data cubes for OLAP (On-Line Analytical Processing) often need to be constructed from data located in several distributed and autonomous information sources. Such a data integration process is challenging due to semantic, syntactic, and structural heterogeneity among the data. While XML (extensible markup language) is the de facto standard for data exchange, the three types of heterogeneity remain. Moreover, popular path-oriented XML query languages, such as XQuery, require the user to know in much detail the structure of the documents to be processed and are, thus, effectively impractical in many real-world data integration tasks. Several Lowest Common Ancestor (LCA)-based XML query evaluation strategies have recently been introduced to provide a more structure-independent way to access XML documents. We shall, however, show that this approach leads in the context of certain - not uncommon - types of XML documents to undesirable results. This article introduces a novel high-level data extraction primitive that utilizes the purpose-built Smallest Possible Context (SPC) query evaluation strategy. We demonstrate, through a system prototype for OLAP data cube construction and a sample application in informetrics, that our approach has real advantages in data integration.

Date

9. 2.2008 17:22:42

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Abstract

The domain of user-oriented and cognitive information retrieval (IR) is first discussed, followed by a discussion on the dimensions and types of models one may build for the domain. The focus of the present entry is on the models of user-oriented and cognitive IR, not on their empirical applications. Several models with different emphases on user-oriented and cognitive IR are presented-ranging from overall approaches and relevance models to procedural models, cognitive models, and task-based models. The present entry does not discuss empirical findings based on the models.

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Abstract

The Discounted Cumulated Impact (DCI) index has recently been proposed for research evaluation. In the present work an earlier dataset by Cronin and Meho (2007) is reanalyzed, with the aim of exemplifying the salient features of the DCI index. We apply the index on, and compare our results to, the outcomes of the Cronin-Meho (2007) study. Both authors and their top publications are used as units of analysis, which suggests that, by adjusting the parameters of evaluation according to the needs of research evaluation, the DCI index delivers data on an author's (or publication's) lifetime impact or current impact at the time of evaluation on an author's (or publication's) capability of inviting citations from highly cited later publications as an indication of impact, and on the relative impact across a set of authors (or publications) over their lifetime or currently.

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Abstract

This article investigates how consistent different newspapers are in their choice of words when writing about the same news events. News articles on the same news events were taken from three Finnish newspapers and compared in regard to their central concepts and words representing the concepts in the news texts. Consistency figures were calculated for each set of three articles (the total number of sets was sixty). Inconsistency in words and concepts was found between news articles from different newspapers. The mean value of consistency calculated on the basis of words was 65 per cent; this however depended on the article length. For short news wires consistency was 83 per cent while for long articles it was only 47 per cent. At the concept level, consistency was considerably higher, ranging from 92 per cent to 97 per cent between short and long articles. The articles also represented three categories of topic (event, process and opinion). Statistically significant differences in consistency were found in regard to length but not in regard to the categories of topic. We argue that the expression inconsistency is a clear sign of a retrieval problem and that query expansion based on semantic relationships can significantly improve retrieval performance on free-text sources.

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Abstract

The study analyses contributions to Library and Information Science (LIS) by researchers representing various disciplines. How are such contributions associated with the choice of research topics and methodology? The study employs a quantitative content analysis of articles published in 31 scholarly LIS journals in 2015. Each article is seen as a contribution to LIS by the authors' disciplines, which are inferred from their affiliations. The unit of analysis is the article-discipline pair. Of the contribution instances, the share of LIS is one third. Computer Science contributes one fifth and Business and Economics one sixth. The latter disciplines dominate the contributions in information retrieval, information seeking, and scientific communication indicating strong influences in LIS. Correspondence analysis reveals three clusters of research, one focusing on traditional LIS with contributions from LIS and Humanities and survey-type research; another on information retrieval with contributions from Computer Science and experimental research; and the third on scientific communication with contributions from Natural Sciences and Medicine and citation analytic research. The strong differentiation of scholarly contributions in LIS hints to the fragmentation of LIS as a discipline.

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Abstract

Purpose This paper analyses the research in Library and Information Science (LIS) and reports on (1) the status of LIS research in 2015 and (2) on the evolution of LIS research longitudinally from 1965 to 2015. Design/methodology/approach The study employs a quantitative intellectual content analysis of articles published in 30+ scholarly LIS journals, following the design by Tuomaala et al. (2014). In the content analysis, we classify articles along eight dimensions covering topical content and methodology. Findings The topical findings indicate that the earlier strong LIS emphasis on L&I services has declined notably, while scientific and professional communication has become the most popular topic. Information storage and retrieval has given up its earlier strong position towards the end of the years analyzed. Individuals are increasingly the units of observation. End-user's and developer's viewpoints have strengthened at the cost of intermediaries' viewpoint. LIS research is methodologically increasingly scattered since survey, scientometric methods, experiment, case studies and qualitative studies have all gained in popularity. Consequently, LIS may have become more versatile in the analysis of its research objects during the years analyzed. Originality/value Among quantitative intellectual content analyses of LIS research, the study is unique in its scope: length of analysis period (50 years), width (8 dimensions covering topical content and methodology) and depth (the annual batch of 30+ scholarly journals).

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Abstract

There is a well-known gap between systems-oriented information retrieval (IR) and user-oriented IR, which cognitive IR seeks to bridge. It is therefore interesting to analyze approaches at the level of frameworks, models, and study designs. This article is an exercise in such an analysis, focusing on two significant approaches to IR: the lab IR approach and P. Ingwersen's (1996) cognitive IR approach. The article focuses on their research frameworks, models, hypotheses, laws and theories, study designs, and possible contributions. The two approaches are quite different, which becomes apparent in the use of Independent, controlled, and dependent variables in the study designs of each approach. Thus, each approach is capable of contributing very differently to understanding and developing information access. The article also discusses integrating the approaches at the study-design level.

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Abstract

In order to design information retrieval (IR) learning environments and instruction, it is important to explore learning outcomes of different pedagogical solutions. Learning outcomes have seldom been evaluated in IR instruction. The particular focus of this study is the assessment of learning outcomes in an experimental, but naturalistic, learning environment compared to more traditional instruction. The 57 participants of an introductory course on IR were selected for this study, and the analysis illustrates their learning outcomes regarding both conceptual change and development of IR skill. Concept mapping of student essays was used to analyze conceptual change and log-files of search exercises provided data for performance assessment. Students in the experimental learning environment changed their conceptions more regarding linguistic aspects of IR and paid more emphasis on planning and management of search process. Performance assessment indicates that anchored instruction and scaffolding with an instructional tool, the IR Game, with performance feedback enables students to construct queries with fewer semantic knowledge errors also in operational IR systems.

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Abstract

In this article, the authors present evaluation results for transitive dictionary-based cross-language information retrieval (CLIR) using graded relevance assessments in a best match retrieval environment. A text database containing newspaper articles and a related set of 35 search topics were used in the tests. Source language topics (in English, German, and Swedish) were automatically translated into the target language (Finnish) via an intermediate (or pivot) language. Effectiveness of the transitively translated queries was compared to that of the directly translated and monolingual Finnish queries. Pseudo-relevance feedback (PRF) was also used to expand the original transitive target queries. Cross-language information retrieval performance was evaluated on three relevance thresholds: stringent, regular, and liberal. The transitive translations performed well achieving, on the average, 85-93% of the direct translation performance, and 66-72% of monolingual performance. Moreover, PRF was successful in raising the performance of transitive translation routes in absolute terms as well as in relation to monolingual and direct translation performance applying PRF.

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Abstract

Modern fact databses contain abundant data classified through several classifications. Typically, users msut consult these classifications in separate manuals or files, thus making their effective use difficult. Contemporary database systems do little support deductive use of classifications. In this study we show how deductive data management techniques can be applied to the utilization of data value classifications. Computation of transitive class relationships is of primary importance here. We define a representation of classifications which supports transitive computation and present an operation-oriented deductive query language tailored for classification-based deductive information retrieval. The operations of this language are on the same abstraction level as relational algebra operations and can be integrated with these to form a powerful and flexible query language for deductive information retrieval. We define the integration of these operations and demonstrate the usefulness of the language in terms of several sample queries

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Abstract

The article by K. Järvelin & O. Persson published in JASIST 59(9), The DCI-Index: Discounted Cumulated Impact-Based Research Evaluation, (pp. 1433-1440) contains an unfortunate error in one of its formulas, Equation 3. The present paper gives the correction and an example of impact analysis based on the corrected formula.

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Abstract

The article presents the search situation transition (SST) method for analysing Web information search (WIS) processes. The idea of the method is to analyse searching behaviour, the process, in detail and connect both the searchers' actions (captured in a log) and his/her intentions and goals, which log analysis never captures. On the other hand, ex post factor surveys, while popular in WIS research, cannot capture the actual search processes. The method is presented through three facets: its domain, its procedure, and its justification. The method's domain is presented in the form of a conceptual framework which maps five central categories that influence WIS processes; the searcher, the social/organisational environment, the work task, the search task, and the process itself. The method's procedure includes various techniques for data collection and analysis. The article presents examples from real WIS processes and shows how the method can be used to identify the interplay of the categories during the processes. It is shown that the method presents a new approach in information seeking and retrieval by focusing on the search process as a phenomenon and by explicating how different information seeking factors directly affect the search process.

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Abstract

This article presents a novel user-oriented interface for generalised informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modelling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible and extensible. It enables end users to perform basic informetric ad hoc calculations easily and often with much less effort than in contemporary online retrieval systems. It also provides several fruitful generalisations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organisations or countries. In the interface, bibliographic data are modelled as complex objects (non-first normal form relations) and terminological and citation networks involving transitive relationships are modelled as binary relations for deductive processing. The interface is flexible, because it makes it easy to switch focus between various object types for informetric calculations, e.g. from authors to institutions. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g. by years or content-bearing attributes. Such modelling allows flexible data aggregation along many dimensions. These salient features emerge from the query interface's general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results in the article.

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Abstract

We analyze barriers to task-based information access in molecular medicine, focusing on research tasks, which provide task performance sessions of varying complexity. Molecular medicine is a relevant domain because it offers thousands of digital resources as the information environment. Data were collected through shadowing of real work tasks. Thirty work task sessions were analyzed and barriers in these identified. The barriers were classified by their character (conceptual, syntactic, and technological) and by their context of appearance (work task, system integration, or system). Also, work task sessions were grouped into three complexity classes and the frequency of barriers of varying types across task complexity levels were analyzed. Our findings indicate that although most of the barriers are on system level, there is a quantum of barriers in integration and work task contexts. These barriers might be overcome through attention to the integrated use of multiple systems at least for the most frequent uses. This can be done by means of standardization and harmonization of the data and by taking the requirements of the work tasks into account in system design and development, because information access is seldom an end itself, but rather serves to reach the goals of work tasks.

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Abstract

Search key resolution power is analyzed in the context of a request, i.e., among the set of search keys for the request. Methods of characterizing the resolution power of keys automatically are studied, and the effects search keys of varying resolution power have on retrieval effectiveness are analyzed. It is shown that it often is possible to identify the best key of a query while the discrimination between the remaining keys presents problems. It is also shown that query performance is improved by suitably using the best key in a structured query. The tests were run with InQuery in a subcollection of the TREC collection, which contained some 515,000 documents

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Abstract

Multidimensional data analysis or On-line analytical processing (OLAP) offers a single subject-oriented source for analyzing summary data based an various dimensions. We demonstrate that the OLAP approach gives a promising starting point for advanced analysis and comparison among summary data in informetrics applications. At the moment there is no single precise, commonly accepted logical/conceptual model for multidimensional analysis. This is because the requirements of applications vary considerably. We develop a conceptual/logical multidimensional model for supporting the complex and unpredictable needs of informetrics. Summary data are considered with respect of some dimensions. By changing dimensions the user may construct other views an the same summary data. We develop a multidimensional query language whose basic idea is to support the definition of views in a way, which is natural and intuitive for lay users in the informetrics area. We show that this view-oriented query language has a great expressive power and its degree of declarativity is greater than in contemporary operation-oriented or SQL (Structured Query Language)-like OLAP query languages.

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Abstract

Purpose - To show that stem generation compares well with lemmatization as a morphological tool for a highly inflectional language for IR purposes in a best-match retrieval system. Design/methodology/approach - Effects of three different morphological methods - lemmatization, stemming and stem production - for Finnish are compared in a probabilistic IR environment (INQUERY). Evaluation is done using a four-point relevance scale which is partitioned differently in different test settings. Findings - Results show that stem production, a lighter method than morphological lemmatization, compares well with lemmatization in a best-match IR environment. Differences in performance between stem production and lemmatization are small and they are not statistically significant in most of the tested settings. It is also shown that hitherto a rather neglected method of morphological processing for Finnish, stemming, performs reasonably well although the stemmer used - a Porter stemmer implementation - is far from optimal for a morphologically complex language like Finnish. In another series of tests, the effects of compound splitting and derivational expansion of queries are tested. Practical implications - Usefulness of morphological lemmatization and stem generation for IR purposes can be estimated with many factors. On the average P-R level they seem to behave very close to each other in a probabilistic IR system. Thus, the choice of the used method with highly inflectional languages needs to be estimated along other dimensions too. Originality/value - Results are achieved using Finnish as an example of a highly inflectional language. The results are of interest for anyone who is interested in processing of morphological variation of a highly inflected language for IR purposes.