Search (34 results, page 2 of 2)

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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

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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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?

Source

New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole

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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

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

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

Purpose - To present a method for creating a comparable document collection from two document collections in different languages. Design/methodology/approach - The best query keys were extracted from a Finnish source collection (articles of the newspaper Aamulehti) with the relative average term frequency formula. The keys were translated into English with a dictionary-based query translation program. The resulting lists of words were used as queries that were run against the target collection (Los Angeles Times articles) with the nearest neighbor method. The documents were aligned with unrestricted and date-restricted alignment schemes, which were also combined. Findings - The combined alignment scheme was found the best, when the relatedness of the document pairs was assessed with a five-degree relevance scale. Of the 400 document pairs, roughly 40 percent were highly or fairly related and 75 percent included at least lexical similarity. Research limitations/implications - The number of alignment pairs was small due to the short common time period of the two collections, and their geographical (and thus, topical) remoteness. In future, our aim is to build larger comparable corpora in various languages and use them as source of translation knowledge for the purposes of cross-language information retrieval (CLIR). Practical implications - Readily available parallel corpora are scarce. With this method, two unrelated document collections can relatively easily be aligned to create a CLIR resource. Originality/value - The method can be applied to weakly linked collections and morphologically complex languages, such as Finnish.

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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.

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Abstract

Purpose - The aim of this paper is to explore the possibility of retrieving information with Kohonen self-organising maps, which are known to be effective to group objects according to their similarity or dissimilarity. Design/methodology/approach - After conventional preprocessing, such as transforming into vector space, documents from a German document collection were trained for a neural network of Kohonen self-organising map type. Such an unsupervised network forms a document map from which relevant objects can be found according to queries. Findings - Self-organising maps ordered documents to groups from which it was possible to find relevant targets. Research limitations/implications - The number of documents used was moderate due to the limited number of documents associated to test topics. The training of self-organising maps entails rather long running times, which is their practical limitation. In future, the aim will be to build larger networks by compressing document matrices, and to develop document searching in them. Practical implications - With self-organising maps the distribution of documents can be visualised and relevant documents found in document collections of limited size. Originality/value - The paper reports on an approach that can be especially used to group documents and also for information search. So far self-organising maps have rarely been studied for information retrieval. Instead, they have been applied to document grouping tasks.

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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

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

In this article the authors look at the prescriptions advocated by Web search textbooks in the light of a selection of empirical data of real Web information search processes. They use the strategy of disjointed incrementalism, which is a theoretical foundation from decision making, to focus an how people face complex problems, and claim that such problem solving can be compared to the tasks searchers perform when interacting with the Web. The findings suggest that textbooks an Web searching should take into account that searchers only tend to take a certain number of sources into consideration, that the searchers adjust their goals and objectives during searching, and that searchers reconsider the usefulness of sources at different stages of their work tasks as well as their search tasks.

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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

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.