Search (36 results, page 1 of 2)

  • × author_ss:"Järvelin, K."
  1. Niemi, T.; Hirvonen, L.; Järvelin, K.: Multidimensional data model and query language for informetrics (2003) 0.02 
    0.019276196 = product of:
  0.086742885 = sum of:
    0.07118686 = weight(_text_:applications in 1753) [ClassicSimilarity], result of:
      0.07118686 = score(doc=1753,freq=4.0), product of:
        0.17247584 = queryWeight, product of:
          4.4025097 = idf(docFreq=1471, maxDocs=44218)
          0.03917671 = queryNorm
        0.41273528 = fieldWeight in 1753, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.4025097 = idf(docFreq=1471, maxDocs=44218)
          0.046875 = fieldNorm(doc=1753)
    0.015556021 = weight(_text_:of in 1753) [ClassicSimilarity], result of:
      0.015556021 = score(doc=1753,freq=12.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.25392252 = fieldWeight in 1753, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=1753)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.10, S.939-951
  2. Saastamoinen, M.; Järvelin, K.: Search task features in work tasks of varying types and complexity (2017) 0.02 
    0.018669177 = product of:
  0.056007527 = sum of:
    0.015556021 = weight(_text_:of in 3589) [ClassicSimilarity], result of:
      0.015556021 = score(doc=3589,freq=12.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.25392252 = fieldWeight in 3589, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=3589)
    0.0245278 = weight(_text_:systems in 3589) [ClassicSimilarity], result of:
      0.0245278 = score(doc=3589,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.2037246 = fieldWeight in 3589, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.046875 = fieldNorm(doc=3589)
    0.015923709 = product of:
      0.031847417 = sum of:
        0.031847417 = weight(_text_:22 in 3589) [ClassicSimilarity], result of:
          0.031847417 = score(doc=3589,freq=2.0), product of:
            0.13719016 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03917671 = queryNorm
            0.23214069 = fieldWeight in 3589, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3589)
      0.5 = coord(1/2)
  0.33333334 = coord(3/9)
    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.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1111-1123
  3. Järvelin, K.; Ingwersen, P.: User-oriented and cognitive models of information retrieval (2009) 0.02 
    0.017083302 = product of:
  0.07687486 = sum of:
    0.05872617 = weight(_text_:applications in 3901) [ClassicSimilarity], result of:
      0.05872617 = score(doc=3901,freq=2.0), product of:
        0.17247584 = queryWeight, product of:
          4.4025097 = idf(docFreq=1471, maxDocs=44218)
          0.03917671 = queryNorm
        0.34048924 = fieldWeight in 3901, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4025097 = idf(docFreq=1471, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3901)
    0.018148692 = weight(_text_:of in 3901) [ClassicSimilarity], result of:
      0.018148692 = score(doc=3901,freq=12.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.29624295 = fieldWeight in 3901, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3901)
  0.22222222 = coord(2/9)
    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.
    Source
    Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
  4. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.02 
    0.016477594 = product of:
  0.04943278 = sum of:
    0.0089812735 = weight(_text_:of in 2230) [ClassicSimilarity], result of:
      0.0089812735 = score(doc=2230,freq=4.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.14660224 = fieldWeight in 2230, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=2230)
    0.0245278 = weight(_text_:systems in 2230) [ClassicSimilarity], result of:
      0.0245278 = score(doc=2230,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.2037246 = fieldWeight in 2230, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.046875 = fieldNorm(doc=2230)
    0.015923709 = product of:
      0.031847417 = sum of:
        0.031847417 = weight(_text_:22 in 2230) [ClassicSimilarity], result of:
          0.031847417 = score(doc=2230,freq=2.0), product of:
            0.13719016 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03917671 = queryNorm
            0.23214069 = fieldWeight in 2230, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2230)
      0.5 = coord(1/2)
  0.33333334 = coord(3/9)
    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
  5. Sormunen, E.; Kekäläinen, J.; Koivisto, J.; Järvelin, K.: Document text characteristics affect the ranking of the most relevant documents by expanded structured queries (2001) 0.01 
    0.011127857 = product of:
  0.050075352 = sum of:
    0.021169065 = weight(_text_:of in 4487) [ClassicSimilarity], result of:
      0.021169065 = score(doc=4487,freq=32.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.34554482 = fieldWeight in 4487, product of:
          5.656854 = tf(freq=32.0), with freq of:
            32.0 = termFreq=32.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4487)
    0.02890629 = weight(_text_:systems in 4487) [ClassicSimilarity], result of:
      0.02890629 = score(doc=4487,freq=4.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.24009174 = fieldWeight in 4487, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4487)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of documentation. 57(2001) no.3, S.358-376
  6. Järvelin, K.; Niemi, T.: Deductive information retrieval based on classifications (1993) 0.01 
    0.009913453 = product of:
  0.044610538 = sum of:
    0.020082738 = weight(_text_:of in 2229) [ClassicSimilarity], result of:
      0.020082738 = score(doc=2229,freq=20.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.32781258 = fieldWeight in 2229, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=2229)
    0.0245278 = weight(_text_:systems in 2229) [ClassicSimilarity], result of:
      0.0245278 = score(doc=2229,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.2037246 = fieldWeight in 2229, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.046875 = fieldNorm(doc=2229)
  0.22222222 = coord(2/9)
    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
    Source
    Journal of the American Society for Information Science. 44(1993) no.10, S.557-578
  7. Halttunen, K.; Järvelin, K.: Assessing learning outcomes in two information retrieval learning environments (2005) 0.01 
    0.009684435 = product of:
  0.04357996 = sum of:
    0.019052157 = weight(_text_:of in 996) [ClassicSimilarity], result of:
      0.019052157 = score(doc=996,freq=18.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.3109903 = fieldWeight in 996, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=996)
    0.0245278 = weight(_text_:systems in 996) [ClassicSimilarity], result of:
      0.0245278 = score(doc=996,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.2037246 = fieldWeight in 996, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.046875 = fieldNorm(doc=996)
  0.22222222 = coord(2/9)
    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.
  8. Kumpulainen, S.; Järvelin, K.: Barriers to task-based information access in molecular medicine (2012) 0.01 
    0.008942596 = product of:
  0.04024168 = sum of:
    0.019801848 = weight(_text_:of in 4965) [ClassicSimilarity], result of:
      0.019801848 = score(doc=4965,freq=28.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.32322758 = fieldWeight in 4965, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4965)
    0.020439833 = weight(_text_:systems in 4965) [ClassicSimilarity], result of:
      0.020439833 = score(doc=4965,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.1697705 = fieldWeight in 4965, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4965)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.86-97
  9. Tuomaala, O.; Järvelin, K.; Vakkari, P.: Evolution of library and information science, 1965-2005 : content analysis of journal articles (2014) 0.01 
    0.008942596 = product of:
  0.04024168 = sum of:
    0.019801848 = weight(_text_:of in 1309) [ClassicSimilarity], result of:
      0.019801848 = score(doc=1309,freq=28.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.32322758 = fieldWeight in 1309, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1309)
    0.020439833 = weight(_text_:systems in 1309) [ClassicSimilarity], result of:
      0.020439833 = score(doc=1309,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.1697705 = fieldWeight in 1309, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1309)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.7, S.1446-1462
  10. Järvelin, K.: ¬An analysis of two approaches in information retrieval : from frameworks to study designs (2007) 0.01 
    0.008907516 = product of:
  0.04008382 = sum of:
    0.015556021 = weight(_text_:of in 326) [ClassicSimilarity], result of:
      0.015556021 = score(doc=326,freq=12.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.25392252 = fieldWeight in 326, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=326)
    0.0245278 = weight(_text_:systems in 326) [ClassicSimilarity], result of:
      0.0245278 = score(doc=326,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.2037246 = fieldWeight in 326, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.046875 = fieldNorm(doc=326)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.7, S.971-986
  11. Ferro, N.; Silvello, G.; Keskustalo, H.; Pirkola, A.; Järvelin, K.: ¬The twist measure for IR evaluation : taking user's effort into account (2016) 0.01 
    0.0084427325 = product of:
  0.037992295 = sum of:
    0.017552461 = weight(_text_:of in 2771) [ClassicSimilarity], result of:
      0.017552461 = score(doc=2771,freq=22.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.28651062 = fieldWeight in 2771, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2771)
    0.020439833 = weight(_text_:systems in 2771) [ClassicSimilarity], result of:
      0.020439833 = score(doc=2771,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.1697705 = fieldWeight in 2771, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2771)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.3, S.620-648
  12. Talvensaari, T.; Juhola, M.; Laurikkala, J.; Järvelin, K.: Corpus-based cross-language information retrieval in retrieval of highly relevant documents (2007) 0.01 
    0.007868583 = product of:
  0.035408624 = sum of:
    0.014968789 = weight(_text_:of in 139) [ClassicSimilarity], result of:
      0.014968789 = score(doc=139,freq=16.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24433708 = fieldWeight in 139, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=139)
    0.020439833 = weight(_text_:systems in 139) [ClassicSimilarity], result of:
      0.020439833 = score(doc=139,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.1697705 = fieldWeight in 139, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.0390625 = fieldNorm(doc=139)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.3, S.322-334
  13. Vakkari, P.; Järvelin, K.; Chang, Y.-W.: ¬The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995-2015 (2023) 0.01 
    0.007349246 = product of:
  0.033071607 = sum of:
    0.019801848 = weight(_text_:of in 998) [ClassicSimilarity], result of:
      0.019801848 = score(doc=998,freq=28.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.32322758 = fieldWeight in 998, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=998)
    0.013269759 = product of:
      0.026539518 = sum of:
        0.026539518 = weight(_text_:22 in 998) [ClassicSimilarity], result of:
          0.026539518 = score(doc=998,freq=2.0), product of:
            0.13719016 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03917671 = queryNorm
            0.19345059 = fieldWeight in 998, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=998)
      0.5 = coord(1/2)
  0.22222222 = coord(2/9)
    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
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.811-827
  14. Järvelin, K.; Ingwersen, P.; Niemi, T.: ¬A user-oriented interface for generalised informetric analysis based on applying advanced data modelling techniques (2000) 0.01 
    0.006894304 = product of:
  0.031024367 = sum of:
    0.010584532 = weight(_text_:of in 4545) [ClassicSimilarity], result of:
      0.010584532 = score(doc=4545,freq=8.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.17277241 = fieldWeight in 4545, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4545)
    0.020439833 = weight(_text_:systems in 4545) [ClassicSimilarity], result of:
      0.020439833 = score(doc=4545,freq=2.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.1697705 = fieldWeight in 4545, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4545)
  0.22222222 = coord(2/9)
    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.
    Source
    Journal of documentation. 56(2000) no.3, S.250-278
  15. Näppilä, T.; Järvelin, K.; Niemi, T.: ¬A tool for data cube construction from structurally heterogeneous XML documents (2008) 0.01 
    0.0055785836 = product of:
  0.025103625 = sum of:
    0.011833867 = weight(_text_:of in 1369) [ClassicSimilarity], result of:
      0.011833867 = score(doc=1369,freq=10.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.19316542 = fieldWeight in 1369, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1369)
    0.013269759 = product of:
      0.026539518 = sum of:
        0.026539518 = weight(_text_:22 in 1369) [ClassicSimilarity], result of:
          0.026539518 = score(doc=1369,freq=2.0), product of:
            0.13719016 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03917671 = queryNorm
            0.19345059 = fieldWeight in 1369, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1369)
      0.5 = coord(1/2)
  0.22222222 = coord(2/9)
    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
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.3, S.435-449
  16. Ingwersen, P.; Järvelin, K.: ¬The turn : integration of information seeking and retrieval in context (2005) 0.01 
    0.0055639283 = product of:
  0.025037676 = sum of:
    0.010584532 = weight(_text_:of in 1323) [ClassicSimilarity], result of:
      0.010584532 = score(doc=1323,freq=32.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.17277241 = fieldWeight in 1323, product of:
          5.656854 = tf(freq=32.0), with freq of:
            32.0 = termFreq=32.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1323)
    0.014453145 = weight(_text_:systems in 1323) [ClassicSimilarity], result of:
      0.014453145 = score(doc=1323,freq=4.0), product of:
        0.12039685 = queryWeight, product of:
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.03917671 = queryNorm
        0.12004587 = fieldWeight in 1323, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.0731742 = idf(docFreq=5561, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1323)
  0.22222222 = coord(2/9)
    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.
  17. Pirkola, A.; Järvelin, K.: Employing the resolution power of search keys (2001) 0.00 
    0.002469724 = product of:
  0.022227516 = sum of:
    0.022227516 = weight(_text_:of in 5907) [ClassicSimilarity], result of:
      0.022227516 = score(doc=5907,freq=18.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.36282203 = fieldWeight in 5907, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5907)
  0.11111111 = coord(1/9)
    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
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.7, S.575-583
  18. Ahlgren, P.; Järvelin, K.: Measuring impact of twelve information scientists using the DCI index (2010) 0.00 
    0.0024443932 = product of:
  0.021999538 = sum of:
    0.021999538 = weight(_text_:of in 3593) [ClassicSimilarity], result of:
      0.021999538 = score(doc=3593,freq=24.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.3591007 = fieldWeight in 3593, product of:
          4.8989797 = tf(freq=24.0), with freq of:
            24.0 = termFreq=24.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=3593)
  0.11111111 = coord(1/9)
    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.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1424-1439
  19. Järvelin, K.; Vakkari, P.: ¬The evolution of library and information science 1965-1985 : a content analysis of journal titles (1993) 0.00 
    0.0023284785 = product of:
  0.020956306 = sum of:
    0.020956306 = weight(_text_:of in 4649) [ClassicSimilarity], result of:
      0.020956306 = score(doc=4649,freq=4.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.34207192 = fieldWeight in 4649, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.109375 = fieldNorm(doc=4649)
  0.11111111 = coord(1/9)
  20. Kekäläinen, J.; Järvelin, K.: Using graded relevance assessments in IR evaluation (2002) 0.00 
    0.002277429 = product of:
  0.02049686 = sum of:
    0.02049686 = weight(_text_:of in 5225) [ClassicSimilarity], result of:
      0.02049686 = score(doc=5225,freq=30.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.33457235 = fieldWeight in 5225, product of:
          5.477226 = tf(freq=30.0), with freq of:
            30.0 = termFreq=30.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5225)
  0.11111111 = coord(1/9)
    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.
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.13, S.1120-xxxx

Authors

Years

Types

  • a 35
  • m 1
  • More… Less…

Themes