Search (20 results, page 1 of 1)

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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 Turn analyzes the research of information seeking and retrieval (IS&R) and proposes a new direction of integrating research in these two areas: the fields should turn off their separate and narrow paths and construct a new avenue of research. An essential direction for this avenue is context as given in the subtitle Integration of Information Seeking and Retrieval in Context. Other essential themes in the book include: IS&R research models, frameworks and theories; search and works tasks and situations in context; interaction between humans and machines; information acquisition, relevance and information use; research design and methodology based on a structured set of explicit variables - all set into the holistic cognitive approach. The present monograph invites the reader into a construction project - there is much research to do for a contextual understanding of IS&R. The Turn represents a wide-ranging perspective of IS&R by providing a novel unique research framework, covering both individual and social aspects of information behavior, including the generation, searching, retrieval and use of information. Regarding traditional laboratory information retrieval research, the monograph proposes the extension of research toward actors, search and work tasks, IR interaction and utility of information. Regarding traditional information seeking research, it proposes the extension toward information access technology and work task contexts. The Turn is the first synthesis of research in the broad area of IS&R ranging from systems oriented laboratory IR research to social science oriented information seeking studies. TOC:Introduction.- The Cognitive Framework for Information.- The Development of Information Seeking Research.- Systems-Oriented Information Retrieval.- Cognitive and User-Oriented Information Retrieval.- The Integrated IS&R Research Framework.- Implications of the Cognitive Framework for IS&R.- Towards a Research Program.- Conclusion.- Definitions.- References.- Index.

Footnote

Rez. in: Mitt. VÖB 59(2006) H.2, S.81-83 (O. Oberhauser): "Mit diesem Band haben zwei herausragende Vertreter der europäischen Informationswissenschaft, die Professoren Peter Ingwersen (Kopenhagen) und Kalervo Järvelin (Tampere) ein Werk vorgelegt, das man vielleicht dereinst als ihr opus magnum bezeichnen wird. Mich würde dies nicht überraschen, denn die Autoren unternehmen hier den ambitionierten Versuch, zwei informations wissenschaftliche Forschungstraditionen, die einander bisher in eher geringem Ausmass begegneten, unter einem gesamtheitlichen kognitiven Ansatz zu vereinen - das primär im sozialwissenschaftlichen Bereich verankerte Forschungsgebiet "Information Seeking and Retrieval" (IS&R) und das vorwiegend im Informatikbereich angesiedelte "Information Retrieval" (IR). Dabei geht es ihnen auch darum, den seit etlichen Jahren zwar dominierenden, aber auch als zu individualistisch kritisierten kognitiven Ansatz so zu erweitern, dass technologische, verhaltensbezogene und kooperative Aspekte in kohärenter Weise berücksichtigt werden. Dies geschieht auf folgende Weise in neun Kapiteln: - Zunächst werden die beiden "Lager" - die an Systemen und Laborexperimenten orientierte IR-Tradition und die an Benutzerfragen orientierte IS&R-Fraktion - einander gegenübergestellt und einige zentrale Begriffe geklärt. - Im zweiten Kapitel erfolgt eine ausführliche Darstellung der kognitiven Richtung der Informationswissenschaft, insbesondere hinsichtlich des Informationsbegriffes. - Daran schliesst sich ein Überblick über die bisherige Forschung zu "Information Seeking" (IS) - eine äusserst brauchbare Einführung in die Forschungsfragen und Modelle, die Forschungsmethodik sowie die in diesem Bereich offenen Fragen, z.B. die aufgrund der einseitigen Ausrichtung des Blickwinkels auf den Benutzer mangelnde Betrachtung der Benutzer-System-Interaktion. - In analoger Weise wird im vierten Kapitel die systemorientierte IRForschung in einem konzentrierten Überblick vorgestellt, in dem es sowohl um das "Labormodell" als auch Ansätze wie die Verarbeitung natürlicher Sprache und Expertensysteme geht. Aspekte wie Relevanz, Anfragemodifikation und Performanzmessung werden ebenso angesprochen wie die Methodik - von den ersten Laborexperimenten bis zu TREC und darüber hinaus.

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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

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

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

Date

29. 9.2001 14:01:42

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Abstract

Research evaluation is increasingly popular and important among research funding bodies and science policy makers. Various indicators have been proposed to evaluate the standing of individual scientists, institutions, journals, or countries. A simple and popular one among the indicators is the h-index, the Hirsch index (Hirsch 2005), which is an indicator for lifetime achievement of a scholar. Several other indicators have been proposed to complement or balance the h-index. However, these indicators have no conception of aging. The AR-index (Jin et al. 2007) incorporates aging but divides the received citation counts by the raw age of the publication. Consequently, the decay of a publication is very steep and insensitive to disciplinary differences. In addition, we believe that a publication becomes outdated only when it is no longer cited, not because of its age. Finally, all indicators treat citations as equally material when one might reasonably think that a citation from a heavily cited publication should weigh more than a citation froma non-cited or little-cited publication.We propose a new indicator, the Discounted Cumulated Impact (DCI) index, which devalues old citations in a smooth way. It rewards an author for receiving new citations even if the publication is old. Further, it allows weighting of the citations by the citation weight of the citing publication. DCI can be used to calculate research performance on the basis of the h-core of a scholar or any other publication data.

Content

Erratum in: Järvelin, K., O. Persson: The DCI-index: discounted cumulated impact-based research evaluation. Erratum re. In: Journal of the American Society for Information Science and Technology. 59(2008) no.14, S.2350-2352.

Object

DCI index

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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.

Object

h-index

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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

Information Retrieval (IR) is a research area both within Computer Science and Information Science. It has by and large two communities: a Computer Science oriented experimental approach and a user-oriented Information Science approach with a Social Science background. The communities hold a critical stance towards each other (e.g., Ingwersen, 1996), the latter suspecting the realism of the former, and the former suspecting the usefulness of the latter. Within Information Science the study of information seeking (IS) also has a Social Science background. There is a lot of research in each of these particular areas of information seeking and retrieval (IS&R). However, the three communities do not really communicate with each other. Why is this, and could the relationships be otherwise? Do the communities in fact belong together? Or perhaps each community is better off forgetting about the existence of the other two? We feel that the relationships between the research areas have not been properly analyzed. One way to analyze the relationships is to examine what each research area is trying to find out: which phenomena are being explained and how. We believe that IS&R research would benefit from being analytic about its frameworks, models and theories, not just at the level of meta-theories, but also much more concretely at the level of study designs. Over the years there have been calls for more context in the study of IS&R. Work tasks as well as cultural activities/interests have been proposed as the proper context for information access. For example, Wersig (1973) conceptualized information needs from the tasks perspective. He argued that in order to learn about information needs and seeking, one needs to take into account the whole active professional role of the individuals being investigated. Byström and Järvelin (1995) analysed IS processes in the light of tasks of varying complexity. Ingwersen (1996) discussed the role of tasks and their descriptions and problematic situations from a cognitive perspective on IR. Most recently, Vakkari (2003) reviewed task-based IR and Järvelin and Ingwersen (2004) proposed the extension of IS&R research toward the task context. Therefore there is much support to the task context, but how should it be applied in IS&R?

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Abstract

We present a novel measure for ranking evaluation, called Twist (t). It is a measure for informational intents, which handles both binary and graded relevance. t stems from the observation that searching is currently a that searching is currently taken for granted and it is natural for users to assume that search engines are available and work well. As a consequence, users may assume the utility they have in finding relevant documents, which is the focus of traditional measures, as granted. On the contrary, they may feel uneasy when the system returns nonrelevant documents because they are then forced to do additional work to get the desired information, and this causes avoidable effort. The latter is the focus of t, which evaluates the effectiveness of a system from the point of view of the effort required to the users to retrieve the desired information. We provide a formal definition of t, a demonstration of its properties, and introduce the notion of effort/gain plots, which complement traditional utility-based measures. By means of an extensive experimental evaluation, t is shown to grasp different aspects of system performances, to not require extensive and costly assessments, and to be a robust tool for detecting differences between systems.

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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.

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Abstract

The increasing flood of documentary information through the Internet and other information sources challenges the developers of information retrieval systems. It is not enough that an IR system is able to make a distinction between relevant and non-relevant documents. The reduction of information overload requires that IR systems provide the capability of screening the most valuable documents out of the mass of potentially or marginally relevant documents. This paper introduces a new concept-based method to analyse the text characteristics of documents at varying relevance levels. The results of the document analysis were applied in an experiment on query expansion (QE) in a probabilistic IR system. Statistical differences in textual characteristics of highly relevant and less relevant documents were investigated by applying a facet analysis technique. In highly relevant documents a larger number of aspects of the request were discussed, searchable expressions for the aspects were distributed over a larger set of text paragraphs, and a larger set of unique expressions were used per aspect than in marginally relevant documents. A query expansion experiment verified that the findings of the text analysis can be exploited in formulating more effective queries for best match retrieval in the search for highly relevant documents. The results revealed that expanded queries with concept-based structures performed better than unexpanded queries or Ñnatural languageÒ queries. Further, it was shown that highly relevant documents benefit essentially more from the concept-based QE in ranking than marginally relevant documents.

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Abstract

We will explore various ways to apply query structuring in cross-language information retrieval. In the first test, English queries were translated into Finnish using an electronic dictionary, and were run in a Finnish newspaper database of 55,000 articles. Queries were structured by combining the Finnish translation equivalents of the same English query key using the syn-operator of the InQuery retrieval system. Structured queries performed markedly better than unstructured queries. Second, the effects of compound-based structuring using a proximity operator for the translation equivalents of query language compound components were tested. The method was not useful in syn-based queries but resulted in decrease in retrieval effectiveness. Proper names are often non-identical spelling variants in different languages. This allows n-gram based translation of names not included in a dictionary. In the third test, a query structuring method where the Boolean and-operator was used to assign more weight to keys translated through n-gram matching gave good results.

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Source

Information processing and management. 29(1993) no.1, S.129-144

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Abstract

Kekalainen and Jarvelin use what they term generalized, nonbinary recall and precision measures where recall is the sum of the relevance scores of the retrieved documents divided by the sum of relevance scores of all documents in the data base, and precision is the sum of the relevance scores of the retrieved documents divided by the number of documents where the relevance scores are real numbers between zero and one. Using the In-Query system and a text data base of 53,893 newspaper articles with 30 queries selected from those for which four relevance categories to provide recall measures were available, search results were evaluated by four judges. Searches were done by average key term weight, Boolean expression, and by average term weight where the terms are grouped by a synonym operator, and for each case with and without expansion of the original terms. Use of higher standards of relevance appears to increase the superiority of the best method. Some methods do a better job of getting the highly relevant documents but do not increase retrieval of marginal ones. There is evidence that generalized precision provides more equitable results, while binary precision provides undeserved merit to some methods. Generally graded relevance measures seem to provide additional insight into IR evaluation.

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Abstract

Information retrieval systems' ability to retrieve highly relevant documents has become more and more important in the age of extremely large collections, such as the World Wide Web (WWW). The authors' aim was to find out how corpus-based cross-language information retrieval (CLIR) manages in retrieving highly relevant documents. They created a Finnish-Swedish comparable corpus from two loosely related document collections and used it as a source of knowledge for query translation. Finnish test queries were translated into Swedish and run against a Swedish test collection. Graded relevance assessments were used in evaluating the results and three relevance criterion levels-liberal, regular, and stringent-were applied. The runs were also evaluated with generalized recall and precision, which weight the retrieved documents according to their relevance level. The performance of the Comparable Corpus Translation system (COCOT) was compared to that of a dictionarybased query translation program; the two translation methods were also combined. The results indicate that corpus-based CUR performs particularly well with highly relevant documents. In average precision, COCOT even matched the monolingual baseline on the highest relevance level. The performance of the different query translation methods was further analyzed by finding out reasons for poor rankings of highly relevant documents.

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Abstract

This article first analyzes library and information science (LIS) research articles published in core LIS journals in 2005. It also examines the development of LIS from 1965 to 2005 in light of comparable data sets for 1965, 1985, and 2005. In both cases, the authors report (a) how the research articles are distributed by topic and (b) what approaches, research strategies, and methods were applied in the articles. In 2005, the largest research areas in LIS by this measure were information storage and retrieval, scientific communication, library and information-service activities, and information seeking. The same research areas constituted the quantitative core of LIS in the previous years since 1965. Information retrieval has been the most popular area of research over the years. The proportion of research on library and information-service activities decreased after 1985, but the popularity of information seeking and of scientific communication grew during the period studied. The viewpoint of research has shifted from library and information organizations to end users and development of systems for the latter. The proportion of empirical research strategies was high and rose over time, with the survey method being the single most important method. However, attention to evaluation and experiments increased considerably after 1985. Conceptual research strategies and system analysis, description, and design were quite popular, but declining. The most significant changes from 1965 to 2005 are the decreasing interest in library and information-service activities and the growth of research into information seeking and scientific communication.

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Date

27.12.2007 11:59:29

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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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Date

22. 6.2023 18:15:06