-
Wildemuth, B.M.; Jacob, E.K.; Fullington, A.;; Bliek, R. de; Friedman, C.P.: ¬A detailed analysis of end-user search behaviours (1991)
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- Imprint
- Medford : Learned Information Inc.
-
Hood, W.W.; Wilson, C.S.: ¬The scatter of documents over databases in different subject domains : how many databases are needed? (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.14, S.1242-1254
-
López-Pujalte, C.; Guerrero-Bote, V.P.; Moya-Anegón, F. de: Order-based fitness functions for genetic algorithms applied to relevance feedback (2003)
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- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.2, S.152-160
-
Greisdorf, H.; O'Connor, B.: Nodes of topicality modeling user notions of on topic documents (2003)
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- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.14, S.1296-1304
-
Radev, D.R.; Libner, K.; Fan, W.: Getting answers to natural language questions on the Web (2002)
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- Source
- Journal of the American Society for Information Science and technology. 53(2002) no.5, S.359-364
-
Kekäläinen, J.; Järvelin, K.: Using graded relevance assessments in IR evaluation (2002)
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- Source
- Journal of the American Society for Information Science and technology. 53(2002) no.13, S.1120-xxxx
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Eastman, C.M.: 30,000 hits may be better than 300 : precision anomalies in Internet searches (2002)
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- Source
- Journal of the American Society for Information Science and Technology. 53(2002) no.11, S.879-882
-
Ménard, E.: Image retrieval : a comparative study on the influence of indexing vocabularies (2009)
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- Abstract
- This paper reports on a research project that compared two different approaches for the indexing of ordinary images representing common objects: traditional indexing with controlled vocabulary and free indexing with uncontrolled vocabulary. We also compared image retrieval within two contexts: a monolingual context where the language of the query is the same as the indexing language and, secondly, a multilingual context where the language of the query is different from the indexing language. As a means of comparison in evaluating the performance of each indexing form, a simulation of the retrieval process involving 30 images was performed with 60 participants. A questionnaire was also submitted to participants in order to gather information with regard to the retrieval process and performance. The results of the retrieval simulation confirm that the retrieval is more effective and more satisfactory for the searcher when the images are indexed with the approach combining the controlled and uncontrolled vocabularies. The results also indicate that the indexing approach with controlled vocabulary is more efficient (queries needed to retrieve an image) than the uncontrolled vocabulary indexing approach. However, no significant differences in terms of temporal efficiency (time required to retrieve an image) was observed. Finally, the comparison of the two linguistic contexts reveal that the retrieval is more effective and more efficient (queries needed to retrieve an image) in the monolingual context rather than the multilingual context. Furthermore, image searchers are more satisfied when the retrieval is done in a monolingual context rather than a multilingual context.
-
Thornley, C.V.; Johnson, A.C.; Smeaton, A.F.; Lee, H.: ¬The scholarly impact of TRECVid (2003-2009) (2011)
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- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.4, S.613-627
-
Bashir, S.; Rauber, A.: On the relationship between query characteristics and IR functions retrieval bias (2011)
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- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1515-1532
-
MacCain, K.W.; White, H.D.; Griffith, B.C.: Comparing retrieval performance in online data bases (1987)
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- Source
- Information processing and management. 23(1987), S.539-553
-
Lu, K.; Kipp, M.E.I.: Understanding the retrieval effectiveness of collaborative tags and author keywords in different retrieval environments : an experimental study on medical collections (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.3, S.483-500
-
Ruthven, I.: Relevance behaviour in TREC (2014)
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- Abstract
- Purpose - The purpose of this paper is to examine how various types of TREC data can be used to better understand relevance and serve as test-bed for exploring relevance. The author proposes that there are many interesting studies that can be performed on the TREC data collections that are not directly related to evaluating systems but to learning more about human judgements of information and relevance and that these studies can provide useful research questions for other types of investigation. Design/methodology/approach - Through several case studies the author shows how existing data from TREC can be used to learn more about the factors that may affect relevance judgements and interactive search decisions and answer new research questions for exploring relevance. Findings - The paper uncovers factors, such as familiarity, interest and strictness of relevance criteria, that affect the nature of relevance assessments within TREC, contrasting these against findings from user studies of relevance. Research limitations/implications - The research only considers certain uses of TREC data and assessment given by professional relevance assessors but motivates further exploration of the TREC data so that the research community can further exploit the effort involved in the construction of TREC test collections. Originality/value - The paper presents an original viewpoint on relevance investigations and TREC itself by motivating TREC as a source of inspiration on understanding relevance rather than purely as a source of evaluation material.
-
Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016)
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- Abstract
- Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.
-
Sarigil, E.; Sengor Altingovde, I.; Blanco, R.; Barla Cambazoglu, B.; Ozcan, R.; Ulusoy, Ö.: Characterizing, predicting, and handling web search queries that match very few or no results (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.2, S.256-270
-
Toepfer, M.; Seifert, C.: Content-based quality estimation for automatic subject indexing of short texts under precision and recall constraints
0.00
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- Abstract
- Semantic annotations have to satisfy quality constraints to be useful for digital libraries, which is particularly challenging on large and diverse datasets. Confidence scores of multi-label classification methods typically refer only to the relevance of particular subjects, disregarding indicators of insufficient content representation at the document-level. Therefore, we propose a novel approach that detects documents rather than concepts where quality criteria are met. Our approach uses a deep, multi-layered regression architecture, which comprises a variety of content-based indicators. We evaluated multiple configurations using text collections from law and economics, where the available content is restricted to very short texts. Notably, we demonstrate that the proposed quality estimation technique can determine subsets of the previously unseen data where considerable gains in document-level recall can be achieved, while upholding precision at the same time. Hence, the approach effectively performs a filtering that ensures high data quality standards in operative information retrieval systems.
