Search (7 results, page 1 of 1)

  • × year_i:[2000 TO 2010}
  • × author_ss:"Järvelin, K."
  1. 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
    0.009625921 = product of:
      0.019251842 = sum of:
        0.019251842 = product of:
          0.038503684 = sum of:
            0.038503684 = weight(_text_:systems in 4487) [ClassicSimilarity], result of:
              0.038503684 = score(doc=4487,freq=4.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = 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)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  2. Näppilä, T.; Järvelin, K.; Niemi, T.: ¬A tool for data cube construction from structurally heterogeneous XML documents (2008) 0.01
    0.008837775 = product of:
      0.01767555 = sum of:
        0.01767555 = product of:
          0.0353511 = sum of:
            0.0353511 = weight(_text_:22 in 1369) [ClassicSimilarity], result of:
              0.0353511 = score(doc=1369,freq=2.0), product of:
                0.1827397 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.052184064 = 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)
      0.5 = coord(1/2)
    
    Date
    9. 2.2008 17:22:42
  3. Järvelin, K.: ¬An analysis of two approaches in information retrieval : from frameworks to study designs (2007) 0.01
    0.008167865 = product of:
      0.01633573 = sum of:
        0.01633573 = product of:
          0.03267146 = sum of:
            0.03267146 = weight(_text_:systems in 326) [ClassicSimilarity], result of:
              0.03267146 = score(doc=326,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = 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)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  4. Halttunen, K.; Järvelin, K.: Assessing learning outcomes in two information retrieval learning environments (2005) 0.01
    0.008167865 = product of:
      0.01633573 = sum of:
        0.01633573 = product of:
          0.03267146 = sum of:
            0.03267146 = weight(_text_:systems in 996) [ClassicSimilarity], result of:
              0.03267146 = score(doc=996,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = 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)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  5. Järvelin, K.; Ingwersen, P.; Niemi, T.: ¬A user-oriented interface for generalised informetric analysis based on applying advanced data modelling techniques (2000) 0.01
    0.0068065543 = product of:
      0.013613109 = sum of:
        0.013613109 = product of:
          0.027226217 = sum of:
            0.027226217 = weight(_text_:systems in 4545) [ClassicSimilarity], result of:
              0.027226217 = score(doc=4545,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = 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)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  6. Talvensaari, T.; Juhola, M.; Laurikkala, J.; Järvelin, K.: Corpus-based cross-language information retrieval in retrieval of highly relevant documents (2007) 0.01
    0.0068065543 = product of:
      0.013613109 = sum of:
        0.013613109 = product of:
          0.027226217 = sum of:
            0.027226217 = weight(_text_:systems in 139) [ClassicSimilarity], result of:
              0.027226217 = score(doc=139,freq=2.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = 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)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  7. Ingwersen, P.; Järvelin, K.: ¬The turn : integration of information seeking and retrieval in context (2005) 0.00
    0.0048129605 = product of:
      0.009625921 = sum of:
        0.009625921 = product of:
          0.019251842 = sum of:
            0.019251842 = weight(_text_:systems in 1323) [ClassicSimilarity], result of:
              0.019251842 = score(doc=1323,freq=4.0), product of:
                0.16037072 = queryWeight, product of:
                  3.0731742 = idf(docFreq=5561, maxDocs=44218)
                  0.052184064 = 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)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.