-
Näppilä, T.; Järvelin, K.; Niemi, T.: ¬A tool for data cube construction from structurally heterogeneous XML documents (2008)
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- 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
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
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- Pages
- S.235-243
- 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
-
Niemi, T.; Junkkari, M.; Järvelin, K.; Viita, S.: Advanced query language for manipulating complex entities (2004)
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- Source
- Information processing and management. 40(2004) no.6, S.869-
-
Pirkola, A.; Hedlund, T.; Keskustalo, H.; Järvelin, K.: Dictionary-based cross-language information retrieval : problems, methods, and research findings (2001)
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- Source
- Information retrieval. 4(2001), S.209-230
-
Ferro, N.; Silvello, G.; Keskustalo, H.; Pirkola, A.; Järvelin, K.: ¬The twist measure for IR evaluation : taking user's effort into account (2016)
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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.
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.3, S.620-648
-
Niemi, T.; Hirvonen, L.; Järvelin, K.: Multidimensional data model and query language for informetrics (2003)
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- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.10, S.939-951
-
Järvelin, K.; Niemi, T.: Deductive information retrieval based on classifications (1993)
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- Source
- Journal of the American Society for Information Science. 44(1993) no.10, S.557-578
-
Kettunen, K.; Kunttu, T.; Järvelin, K.: To stem or lemmatize a highly inflectional language in a probabilistic IR environment? (2005)
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- Source
- Journal of documentation. 61(2005) no.4, S.476-496
-
Järvelin, K.; Ingwersen, P.; Niemi, T.: ¬A user-oriented interface for generalised informetric analysis based on applying advanced data modelling techniques (2000)
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- Source
- Journal of documentation. 56(2000) no.3, S.250-278
-
Talvensaari, T.; Laurikkala, J.; Järvelin, K.; Juhola, M.: ¬A study on automatic creation of a comparable document collection in cross-language information retrieval (2006)
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- Source
- Journal of documentation. 62(2006) no.3, S.372-387
-
Talvensaari, T.; Juhola, M.; Laurikkala, J.; Järvelin, K.: Corpus-based cross-language information retrieval in retrieval of highly relevant documents (2007)
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- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.3, S.322-334
-
Saastamoinen, M.; Järvelin, K.: Search task features in work tasks of varying types and complexity (2017)
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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.
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1111-1123
-
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)
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- Date
- 22. 6.2023 18:15:06
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.7, S.811-827
-
Kristensen, J.; Järvelin, K.: ¬The effectiveness of a searching thesaurus in free-text searching in a full-text database (1990)
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- Source
- International classification. 17(1990), S.77-84
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Järvelin, K.; Persson, O.: ¬The DCI-index : discounted cumulated impact-based research evaluation (2008)
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Järvelin, K.; Persson, O.: ¬The DCI index : discounted cumulated impact-based research evaluation (2008)
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Kumpulainen, S.; Järvelin, K.: Barriers to task-based information access in molecular medicine (2012)
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Pirkola, A.; Järvelin, K.: Employing the resolution power of search keys (2001)
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