Academic literature on the topic 'Contextual search'
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Journal articles on the topic "Contextual search"
Kiran, Rathi, and Mitula Pandya. "Contextual Search Results Clustering Using Lingo with Synonymity." International Journal of Scientific Research 2, no. 6 (June 1, 2012): 183–85. http://dx.doi.org/10.15373/22778179/june2013/58.
Full textAbdolmaleki, Abbas, David Simões, Nuno Lau, Luís Paulo Reis, and Gerhard Neumann. "Contextual Direct Policy Search." Journal of Intelligent & Robotic Systems 96, no. 2 (January 8, 2019): 141–57. http://dx.doi.org/10.1007/s10846-018-0968-4.
Full textMelucci, Massimo. "Contextual Search: A Computational Framework." Foundations and Trends® in Information Retrieval 6, no. 4-5 (2012): 257–405. http://dx.doi.org/10.1561/1500000023.
Full textToh, Yi Ni, Caitlin A. Sisk, and Yuhong V. Jiang. "Contextual cueing in preview search." Attention, Perception, & Psychophysics 82, no. 6 (June 1, 2020): 2862–75. http://dx.doi.org/10.3758/s13414-020-02052-9.
Full textToh, Yi Ni, Caitlin A. Sisk, and Yuhong V. Jiang. "Contextual cueing in preview search." Journal of Vision 20, no. 11 (October 20, 2020): 1259. http://dx.doi.org/10.1167/jov.20.11.1259.
Full textHodsoll, John P., and Glyn W. Humphreys. "Preview Search and Contextual Cuing." Journal of Experimental Psychology: Human Perception and Performance 31, no. 6 (2005): 1346–58. http://dx.doi.org/10.1037/0096-1523.31.6.1346.
Full textHoffmann, Joachim, and Albrecht Sebald. "Local Contextual Cuing in Visual Search." Experimental Psychology 52, no. 1 (January 2005): 31–38. http://dx.doi.org/10.1027/1618-3169.52.1.31.
Full textWalenchok, S., M. Hout, and S. Goldinger. "Categorical Contextual Cueing in Visual Search." Journal of Vision 14, no. 10 (August 22, 2014): 1074. http://dx.doi.org/10.1167/14.10.1074.
Full textNabeta, Tomohiro, Fuminori Ono, and Jun-Ichiro Kawahara. "Transfer of Spatial Context from Visual to Haptic Search." Perception 32, no. 11 (November 2003): 1351–58. http://dx.doi.org/10.1068/p5135.
Full textYang, Xi, Xinbo Gao, Bin Song, and Dong Yang. "Aurora image search with contextual CNN feature." Neurocomputing 281 (March 2018): 67–77. http://dx.doi.org/10.1016/j.neucom.2017.11.059.
Full textDissertations / Theses on the topic "Contextual search"
Lakshmanan, Hariharan 1980. "A client side tool for contextual Web search." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/29385.
Full textIncludes bibliographical references (p. 76-77).
This thesis describes the design and development of an application that uses information relevant to the context of a web search for the purpose of improving the search results obtained using standard search engines. The representation of the contextual information is based on a Vector Space Model and is obtained from a set of documents that have been identified as relevant to the context of the search. Two algorithms have been developed for using this contextual representation to re-rank the search results obtained using search engines. In the first algorithm, re-ranking is done based on a comparison of every search result with all the contextual documents. In the second algorithm, only a subset of the contextual documents that relate to the search query is used to measure the relevance of the search results. This subset is identified by mapping the search query onto the Vector Space representation of the contextual documents. A software application was developed using the .NET framework with C# as the implementation language. The software has functionality to enable users to identify contextual documents and perform searches either using a standard search engine or using the above-mentioned algorithms. The software implementation details, and preliminary results regarding the efficiency of the proposed algorithms have been presented.
by Hariharan Lakshmanan.
S.M.
Limbu, Dilip Kumar. "Contextual information retrieval from the WWW." Click here to access this resource online, 2008. http://hdl.handle.net/10292/450.
Full textFiske, Steven William. "Does Crowding Obscure the Presence of Attentional Guidance in Contextual Cueing?" Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4039.
Full textKarlsson, Michael. "Bathroom Hideouts : A search for new ways of storing." Thesis, Linnéuniversitetet, Institutionen för design, DE, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-14163.
Full textZhang, Limin. "Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype." Diss., Tucson, Arizona : University of Arizona, 2006. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1602%5F1%5Fm.pdf&type=application/pdf.
Full textChimfwembe, Richard. "Pastoral care in a context of poverty : a search for a Zambian contextual church response." Thesis, University of Pretoria, 2013. http://hdl.handle.net/2263/40203.
Full textThesis (PhD)--University of Pretoria, 2013.
gm2014
Practical Theology
unrestricted
Poulet, Sarah. "Contextual Cueing : apprentissage des régularités spatiales de l’environnement au cours de la recherche visuelle et accès conscient aux connaissances." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCC027.
Full textWhile deeply complex, the visual world is highly structured and redundant. Through experience, human beings can thus learn regularities present in the visual world, and exploit them to deal with information overload and facilitate behaviors. For the past twenty years, the Contextual Cueing (CC) paradigm has provided an experimental tool to study, in the laboratory, how spatial regularities can be learned to expedite visual search. The first part of this dissertation reviews the existing literature related to this paradigm. It mainly discusses the implicit nature of CC, the characterization of the acquired knowledge and its facilitating effect, as well as the generalization of spatial CC to other regularities and environments. In a second part, three experimental studies using the CC paradigm are presented. The first one shows that, in natural scenes, the acquisition of implicit knowledge tends to precede the conscious exploitation of regularities that classically accompanies CC in this type of environment. In artificial scenes (i.e., letter configurations), even if CC does not seem to primarily depend on the proper implementation of explicit and conscious processes, our second study reports that its integrity is threatened during normal ageing. Finally, our third study investigates whether CC can emerge from very brief exposures of regularities (i.e., 50ms), and suggests that regularities can actually be extracted and exploited even though search displays are not (physically) available long enough to complete the search
Reuter, Robert. "Direct and indirect measures of learning in visual search." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209542.
Full textand (4) to investigate whether such knowledge about the association between visual contexts and “meaningful” locations can be (automatically) transferred to other tasks, namely a change detection task.
In a first series of four experiments, we tried to replicate the documented contextual cueing effect using a wide range of various direct measures of learning (tasks that are supposed to be related to explicit knowledge) and we systematically varied the distinctiveness of context configurations to study its effect on both direct and indirect measures of learning.
We also ran a series of neural network simulations (briefly described in the general discussion of this thesis), based on a very simple association-learning mechanism, that not only account for the observed contextual cueing effect, but also yield rather specific predictions about future experimental data: contextual cueing effects should also be observed when repetitions of context configurations are not perfect, i.e. the networks were able to react to slightly distorted versions of repeating contexts in a similar way than they did to completely identical contexts. Human participants, we conjectured, should therefore (if the simple connectionist model captures some relevant aspects of the contextual cueing effect) become faster at detecting targets surrounded by context configurations that are only partially identical from trial to trial compared to those trials where the context configurations were randomly generated. These predictions were tested in a second series of experiments using pseudo-repeated context configurations, where some distractor items were either displaced from trial to trial or their orientation changed, while conserving their global layout.
In a third series of experiments, we used more realistic images of natural landscapes as background contexts to establish the robustness of the contextual cueing effect as well as its ecological relevance claimed by Chun and colleagues. We furthermore added a second task to these experiments to study whether the acquired knowledge about the background-target location associations would (automatically) transfer to another visual search task, namely a change detection task. If participants have learned that certain locations of the repeated images are “important”, since they contain the target item to look for, then changes occurring at those specific locations should lead to less “change blindness” than changes occurring at other irrelevant locations. We used two different types of instructions to introduce this second task after the visual search task, where we either stressed the link between the two tasks, i.e. telling them that remembering the “important” locations for each image could be used to find the changes faster, or we simply told them to perform the second task without any reference to the first one.
We will close this thesis with a general discussion, combining findings based on our review of the existing research literature and findings based on our own experimental explorations of the contextual cueing effect. By this we will discuss the implications of our empirical studies for the scientific investigation of contextual cueing and implicit learning, in terms of theoretical, empirical and methodological issues.
Doctorat en sciences psychologiques
info:eu-repo/semantics/nonPublished
Zang, Xuelian [Verfasser], and Hermann J. [Akademischer Betreuer] Müller. "Differential contributions of global, local and background contexts in contextual-guided visual search / Xuelian Zang. Betreuer: Hermann J. Müller." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2014. http://d-nb.info/1076471927/34.
Full textZimák, Radek. "Podnikatelský záměr v oblasti českého internetu včetně realizace." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-75989.
Full textBooks on the topic "Contextual search"
Zikic, Jelena, Derin Kent, and Julia Richardson. International Job Search. Edited by Ute-Christine Klehe and Edwin van Hooft. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764921.013.018.
Full textvan Hooft, Edwin. Motivation and Self-Regulation in Job Search: A Theory of Planned Job Search Behavior. Edited by Ute-Christine Klehe and Edwin van Hooft. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199764921.013.010.
Full textThe Encounter Between Christian and Traditional African Spiritualities in Malawi: The Search for a Contextual Lomwe Christian Spirituality. Edwin Mellen Pr, 2007.
Find full textAnderson, James A. Return to Cognitive Science. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.003.0016.
Full textRascaroli, Laura. Framing. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190238247.003.0008.
Full textKöllner, Patrick, Rudra Sil, and Ariel I. Ahram. Comparative Area Studies. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190846374.003.0001.
Full textArgote, Linda, and John M. Levine, eds. The Oxford Handbook of Group and Organizational Learning. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190263362.001.0001.
Full textFridlund, Mats, Mila Oiva, and Petri Paju, eds. Digital Histories: Emergent Approaches within the New Digital History. Helsinki University Press, 2020. http://dx.doi.org/10.33134/hup-5.
Full textCoates, Ruth. Deification in Russian Religious Thought. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198836230.001.0001.
Full textBook chapters on the topic "Contextual search"
Kiseleva, Julia, Jaap Kamps, and Charles L. A. Clarke. "Contextual Search and Exploration." In Communications in Computer and Information Science, 3–23. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41718-9_1.
Full textPasi, Gabriella. "Contextual Search: Issues and Challenges." In Lecture Notes in Computer Science, 23–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25364-5_3.
Full textRanpara, Ripal, and C. K. Kumbharana. "Contextual Information Retrieval Search Engine Challenges." In Rising Threats in Expert Applications and Solutions, 269–73. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6014-9_31.
Full textUrbain, Jay, and Ophir Frieder. "Exploring Contextual Models in Chemical Patent Search." In Advances in Multidisciplinary Retrieval, 60–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13084-7_6.
Full textLytvyn, Vasyl, Victoria Vysotska, Yevhen Burov, Oleh Veres, and Ihor Rishnyak. "The Contextual Search Method Based on Domain Thesaurus." In Advances in Intelligent Systems and Computing II, 310–19. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70581-1_22.
Full textMohammed, Nazim Uddin, Trong Hai Duong, and Geun Sik Jo. "Contextual Information Search Based on Ontological User Profile." In Computational Collective Intelligence. Technologies and Applications, 490–500. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16732-4_52.
Full textGregory, Lee, and Josef Kittler. "Using Graph Search Techniques for Contextual Colour Retrieval." In Lecture Notes in Computer Science, 186–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-70659-3_19.
Full textAguiar, Fernando. "Improving Web Search by the Identification of Contextual Information." In Intelligent Exploration of the Web, 197–224. Heidelberg: Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-7908-1772-0_13.
Full textRimmel, Arpad, and Fabien Teytaud. "Multiple Overlapping Tiles for Contextual Monte Carlo Tree Search." In Applications of Evolutionary Computation, 201–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12239-2_21.
Full textWeerkamp, Wouter, Krisztian Balog, and Maarten de Rijke. "Using Contextual Information to Improve Search in Email Archives." In Lecture Notes in Computer Science, 400–411. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00958-7_36.
Full textConference papers on the topic "Contextual search"
Abdolmaleki, Abbas, Nuno Lau, Luis Paulo Reis, and Gerhard Neumann. "Contextual Stochastic Search." In GECCO '16: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908961.2909012.
Full textLu, Wenhao, Jingdong Wang, Xian-Sheng Hua, Shengjin Wang, and Shipeng Li. "Contextual image search." In the 19th ACM international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2072298.2072365.
Full textChen, Jay, Brendan Linn, and Lakshminarayanan Subramanian. "SMS-based contextual web search." In the 1st ACM workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1592606.1592611.
Full textAhn, Jinhyun, Hyosook Jung, Heejin Kim, Dongeun Sun, and Seongbin Park. "A System for Contextual Search." In 2008 IEEE International Workshop on Semantic Computing and Applications (IWSCA). IEEE, 2008. http://dx.doi.org/10.1109/iwsca.2008.20.
Full textAbdolmaleki, Abbas, Nuno Lau, Luis Paulo Reis, and Gerhard Neumann. "Non-parametric contextual stochastic search." In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016. http://dx.doi.org/10.1109/iros.2016.7759411.
Full textPaes Leme, Renato, and Jon Schneider. "Contextual Search via Intrinsic Volumes." In 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2018. http://dx.doi.org/10.1109/focs.2018.00034.
Full textYucel, Sakir. "Contextual Search for Software Engineering." In 2016 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2016. http://dx.doi.org/10.1109/csci.2016.0092.
Full textLi, Cheng-Te, and Man-Kwan Shan. "X2-Search: Contextual Expert Search in Social Networks." In 2013 Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2013. http://dx.doi.org/10.1109/taai.2013.44.
Full textde la Higuera, Colin, and Luisa Micó. "A Contextual Normalised Edit Distance." In 2008 First International Workshop on Similarity Search and Applications (SISAP '08). IEEE, 2008. http://dx.doi.org/10.1109/sisap.2008.17.
Full textLimbu, Dilip K., Andrew M. Connor, Russel Pears, and Stephen G. MacDonell. "Improving Web Search Using Contextual Retrieval." In 2009 Sixth International Conference on Information Technology: New Generations. IEEE, 2009. http://dx.doi.org/10.1109/itng.2009.133.
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