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Simple Search
Hits 1 – 11 of 11
1
Investigating collaboration in ubiquitous computing research [<Journal>]
Li, Qingyang
[Verfasser];
Yu, Zhiwen
[Verfasser];
Yi, Fei
[Verfasser].
DNB Subject Category Language
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2
Ten scientific problems in human behavior understanding [<Journal>]
Yu, Zhiwen
[Verfasser];
Du, He
[Verfasser];
Yi, Fei
[Verfasser].
DNB Subject Category Language
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3
Additional file 1: of Prevalence of severe fever with thrombocytopenia syndrome virus in animals in Henan Province, China ...
Huang, Xue-Yong
;
Du, Yan-Hua
;
Wang, Hai-Feng
. - : figshare, 2019
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4
Additional file 1: of Prevalence of severe fever with thrombocytopenia syndrome virus in animals in Henan Province, China ...
Huang, Xue-Yong
;
Du, Yan-Hua
;
Wang, Hai-Feng
. - : figshare, 2019
BASE
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5
Robust eye coding mechanisms in humans during face detection
Yi, Fei
. - 2018
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6
Acculturative stress, meaning-in-life, collectivistic coping, and subjective well-being among Chinese international students: A moderated mediation model
Yi, Fei
In: Graduate Theses and Dissertations (2017)
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7
Designing immersive language learning environments in virtual worlds
Wang, Yi Fei
. - : University of British Columbia, 2012
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8
Designing immersive language learning environments in virtual worlds
Wang, Yi Fei
. - : University of British Columbia, 2012
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9
Designing immersive language learning environments in virtual worlds
Wang, Yi Fei
. - : University of British Columbia, 2012
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10
Using contextual and lexical information to map terms of schemas
Université Montpellier
;
Stagiaire Tang
;
Yi Fei
;
Encadrement Zohra Bellahsène
;
Mathieu Roche
In: http://www.lirmm.fr/~mroche/Recherche/PropositionStagesMontpellier/RapportsStages/rapportStage_YiFei.pdf
Abstract:
It exist many methods of research of similarities between the elements in the schemas. Traditional measurements are based on the similarity between the strings. Such measurements are founded on the following intuition: more the strings characterizing the terms are similar, more “semantically ” close these terms are. The calculation of these measurements is based on operations of suppressions, insertions, substitutions and comparisons of subsequences (N-grams). One of these measurements in the literature is the distance Levenshtein defined as the minimum number of insertions, deletions or substitutions necessary to transform one string into another. For example, such a measurement can prove powerful to find the similarity with abbreviations (like: int/integer). Such a technique can assign a measure distance raised between semantically close terms but having very different strings (lexical), (like: auto/car). Thus, we proposed a new approach to avoid such a problem by studying the context of the term. Within the framework of the mapping of elements of schema, the context of an element can represent the under-trees of an element (context descendent), key words characterizing it, etc. In our approach, each element will be represented by a vector. And the vector represents the context (elements of the under-trees, etc) of the element The algorithm Approxivect that we proposed to solve this problem consists in determining the similarity between two vectors in order to determine the semantic proximity between the elements. Such an approach takes the techniques of search for similarities between documents as a starting point. The Approxivect algorithm also takes into account the proximity of the strings in the contexts as well as the semantic
URL:
http://www.lirmm.fr/~mroche/Recherche/PropositionStagesMontpellier/RapportsStages/rapportStage_YiFei.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.397.1542
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11
Using Learning Analytics to Understand the Design of an Intelligent Language Tutor – Chatbot Lucy
Yi Fei Wang
;
Stephen Petrina
In: http://thesai.org/Downloads/Volume4No11/Paper_17-Using_Learning_Analytics_to_Understand_the_Design_of_an_Intelligent_Language_Tutor.pdf
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