Nowadays,Internet of Things(IoT)is widely deployed and brings great opportunities to change people's daily life.To realize more effective human-computer interaction in the IoT applications,the Question Answering(Q...Nowadays,Internet of Things(IoT)is widely deployed and brings great opportunities to change people's daily life.To realize more effective human-computer interaction in the IoT applications,the Question Answering(QA)systems implanted in the IoT services are supposed to improve the ability to understand natural language.Therefore,the distributed representation of words,which contains more semantic or syntactic information,has been playing a more and more important role in the QA systems.However,learning high-quality distributed word vectors requires lots of storage and computing resources,hence it cannot be deployed on the resource-constrained IoT devices.It is a good choice to outsource the data and computation to the cloud servers.Nevertheless,it could cause privacy risks to directly upload private data to the untrusted cloud.Therefore,realizing the word vector learning process over untrusted cloud servers without privacy leakage is an urgent and challenging task.In this paper,we present a novel efficient word vector learning scheme over encrypted data.We first design a series of arithmetic computation protocols.Then we use two non-colluding cloud servers to implement high-quality word vectors learning over encrypted data.The proposed scheme allows us to perform training word vectors on the remote cloud servers while protecting privacy.Security analysis and experiments over real data sets demonstrate that our scheme is more secure and efficient than existing privacy-preserving word vector learning schemes.展开更多
The present study, using quantitative and qualitative analyses, aimed at delineating the interrelationship between the knowledge of metacognition and the regulation of metacognition, along with the role of learners＇ ...The present study, using quantitative and qualitative analyses, aimed at delineating the interrelationship between the knowledge of metacognition and the regulation of metacognition, along with the role of learners＇ regulatory ability in mediating the effects of task-induced involvement load on word learning. A total of 60 university EFL students were recruited to the study. They first completed a checklist on metacognition and were then assigned to complete three tasks with varying degrees of involvement load followed by a vocabulary test. Of them, 12 students also participated in an interview. The results showed that the two main components of metacognition, i.e., the knowledge and regulation of metacognition, are closely and significantly correlated. The learners, assigned to four different ability groups （LK/LR, LK/HR, HK/LR, HK/HR）, were found to benefit most by engaging in a task with the highest involvement load. Despite the benefits, their regulatory ability mediated the effects of task-induced involvement load on word learning, which was corroborated by the interview results. The relevant implications for teaching and learning words through tasks are further discussed.展开更多
This study investigates how orthographic,semantic and contextual variables—including word length,concreteness,and contextual support—impact on the processing and learning of new words in a second language(L2)when fi...This study investigates how orthographic,semantic and contextual variables—including word length,concreteness,and contextual support—impact on the processing and learning of new words in a second language(L2)when first encountered during reading.Students learning English as a foreign language(EFL)were recruited to read sentences for comprehension,embedded with unfamiliar L2 words that occurred once.Immediately after this,they received a form recognition test,a meaning recall test,and a meaning recognition test.Eye-movement data showed significant effects of word length on both early and late processing of novel words,along with effects of concreteness only on late-processing eye-tracking measures.Informative contexts were read slower than neutral contexts,yet contextual support did not show any direct influence on the processing of novel words.Interestingly,initial learning of abstract words was better than concrete words in terms of form and meaning recognition.Attentional processing of novel L2 words,operationalized by total reading time,positively predicted L2 learners’recognition of new orthographic forms.Taken together,these results suggest:1)orthographic,semantic and contextual factors play distinct roles for initial processing and learning of novel words;2)online processing of novel words contributes to L2 learners’initial knowledge of unfamiliar lexical items acquired from reading.展开更多
The present study aimed to investigate the application of the CLAN （Computerized Language Analysis） program in the CHILDES （Child Language Data Exchange System） on shared and unique words between storybooks. Sixty...The present study aimed to investigate the application of the CLAN （Computerized Language Analysis） program in the CHILDES （Child Language Data Exchange System） on shared and unique words between storybooks. Sixty sixth-grade Chinese-speaking children at an elementary school in Taipei City were recruited. Forty-four three-level of storybooks from Kizclub were collected and analyzed. Fifteen minutes reading instruction was followed by the use of CLAN on storybooks for 25 minutes. Children were given written and spoken vocabulary tests after each cluster of storybook reading period. There were three main findings of the study. First, young EFL （English as a Foreign Language） learners＇ word learning was enhanced through multiple exposures to the shared and unique words from the storybooks. Second, word instruction in isolation prompted written and spoken word learning beyond word instruction in context and repeated reading. Third, the results had pedagogical implications on the value and feasibility of language teaching with storybooks in promoting EFL students＇ word learning by using CLAN, and the limitations of the study were provided.展开更多
It is a known fact that monolingual children will take advantage of the principle of mutual exclusivity(ME)in the process of early word learning,i.e.,the names of two different objects are mutually exclusive(one label...It is a known fact that monolingual children will take advantage of the principle of mutual exclusivity(ME)in the process of early word learning,i.e.,the names of two different objects are mutually exclusive(one label for one referent).With the help of ME,they can expand their vocabulary effectively with a rapid speed.However,for bilingual children,it seems this principle is not that friendly to them,since they are exposed to two languages at the same time,so there could be at least two labels for the same referent.Hence bilingual children may be confused and encounter difficulties in learning words,which will slower their word learning process.This paper tries to,based on earlier research,probe into the question that how bilingual children acquire words without the help of ME,and explore whether there are advantages of not using ME in word learning for bilingual children.展开更多
The word processing depth hypothesis implies a positive association between learners＇ word processing and their lexical learning. In research, learners＇ task-inherent involvement load （i.e., word processing） has n...The word processing depth hypothesis implies a positive association between learners＇ word processing and their lexical learning. In research, learners＇ task-inherent involvement load （i.e., word processing） has not been found to be consistently associated with their lexical learning. Meanwhile, existing studies have not obtained consensus results, either, from directly associating learners＇ actual word processing and their lexical learning. Against this backdrop, this paper reports a study investigating the association between Chinese EFL learners＇ actual word processing and their lexical learning in performing a collaborative oral output task. Interactional and statistical analyses revealed that the participants engaged in four types of word processing; their overall word processing was significantly correlated with both their productive and receptive word acquisition and retention; their different types of word processing were significantly correlated with their productive word learning, but showed variances in correlations with their receptive word learning. The findings were discussed from the perspectives of word processing in collaborative output, word processing and lexical learning, and word processing and different modes of lexical learning.展开更多
Word embedding has drawn a lot of attention due to its usefulness in many NLP tasks. So far a handful of neural-network based word embedding algorithms have been proposed without considering the effects of pronouns in...Word embedding has drawn a lot of attention due to its usefulness in many NLP tasks. So far a handful of neural-network based word embedding algorithms have been proposed without considering the effects of pronouns in the training corpus. In this paper, we propose using co-reference resolution to improve the word embedding by extracting better context. We evaluate four word embeddings with considerations of co-reference resolution and compare the quality of word embedding on the task of word analogy and word similarity on multiple data sets.Experiments show that by using co-reference resolution, the word embedding performance in the word analogy task can be improved by around 1.88%. We find that the words that are names of countries are affected the most,which is as expected.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61672195,61872372the Open Foundation of State Key Laboratory of Cryptology No.MMKFKT201617the National University of Defense Technology Grant No.ZK19-38.
文摘Nowadays,Internet of Things(IoT)is widely deployed and brings great opportunities to change people's daily life.To realize more effective human-computer interaction in the IoT applications,the Question Answering(QA)systems implanted in the IoT services are supposed to improve the ability to understand natural language.Therefore,the distributed representation of words,which contains more semantic or syntactic information,has been playing a more and more important role in the QA systems.However,learning high-quality distributed word vectors requires lots of storage and computing resources,hence it cannot be deployed on the resource-constrained IoT devices.It is a good choice to outsource the data and computation to the cloud servers.Nevertheless,it could cause privacy risks to directly upload private data to the untrusted cloud.Therefore,realizing the word vector learning process over untrusted cloud servers without privacy leakage is an urgent and challenging task.In this paper,we present a novel efficient word vector learning scheme over encrypted data.We first design a series of arithmetic computation protocols.Then we use two non-colluding cloud servers to implement high-quality word vectors learning over encrypted data.The proposed scheme allows us to perform training word vectors on the remote cloud servers while protecting privacy.Security analysis and experiments over real data sets demonstrate that our scheme is more secure and efficient than existing privacy-preserving word vector learning schemes.
基金supported by the Fund Program of Education Sciences Planning in Hainan Province(Grant No.QJY13516004)Key research program of higher education in Hainan province(Grant number:HNJG2014-04)
文摘The present study, using quantitative and qualitative analyses, aimed at delineating the interrelationship between the knowledge of metacognition and the regulation of metacognition, along with the role of learners＇ regulatory ability in mediating the effects of task-induced involvement load on word learning. A total of 60 university EFL students were recruited to the study. They first completed a checklist on metacognition and were then assigned to complete three tasks with varying degrees of involvement load followed by a vocabulary test. Of them, 12 students also participated in an interview. The results showed that the two main components of metacognition, i.e., the knowledge and regulation of metacognition, are closely and significantly correlated. The learners, assigned to four different ability groups （LK/LR, LK/HR, HK/LR, HK/HR）, were found to benefit most by engaging in a task with the highest involvement load. Despite the benefits, their regulatory ability mediated the effects of task-induced involvement load on word learning, which was corroborated by the interview results. The relevant implications for teaching and learning words through tasks are further discussed.
文摘This study investigates how orthographic,semantic and contextual variables—including word length,concreteness,and contextual support—impact on the processing and learning of new words in a second language(L2)when first encountered during reading.Students learning English as a foreign language(EFL)were recruited to read sentences for comprehension,embedded with unfamiliar L2 words that occurred once.Immediately after this,they received a form recognition test,a meaning recall test,and a meaning recognition test.Eye-movement data showed significant effects of word length on both early and late processing of novel words,along with effects of concreteness only on late-processing eye-tracking measures.Informative contexts were read slower than neutral contexts,yet contextual support did not show any direct influence on the processing of novel words.Interestingly,initial learning of abstract words was better than concrete words in terms of form and meaning recognition.Attentional processing of novel L2 words,operationalized by total reading time,positively predicted L2 learners’recognition of new orthographic forms.Taken together,these results suggest:1)orthographic,semantic and contextual factors play distinct roles for initial processing and learning of novel words;2)online processing of novel words contributes to L2 learners’initial knowledge of unfamiliar lexical items acquired from reading.
文摘The present study aimed to investigate the application of the CLAN （Computerized Language Analysis） program in the CHILDES （Child Language Data Exchange System） on shared and unique words between storybooks. Sixty sixth-grade Chinese-speaking children at an elementary school in Taipei City were recruited. Forty-four three-level of storybooks from Kizclub were collected and analyzed. Fifteen minutes reading instruction was followed by the use of CLAN on storybooks for 25 minutes. Children were given written and spoken vocabulary tests after each cluster of storybook reading period. There were three main findings of the study. First, young EFL （English as a Foreign Language） learners＇ word learning was enhanced through multiple exposures to the shared and unique words from the storybooks. Second, word instruction in isolation prompted written and spoken word learning beyond word instruction in context and repeated reading. Third, the results had pedagogical implications on the value and feasibility of language teaching with storybooks in promoting EFL students＇ word learning by using CLAN, and the limitations of the study were provided.
文摘It is a known fact that monolingual children will take advantage of the principle of mutual exclusivity(ME)in the process of early word learning,i.e.,the names of two different objects are mutually exclusive(one label for one referent).With the help of ME,they can expand their vocabulary effectively with a rapid speed.However,for bilingual children,it seems this principle is not that friendly to them,since they are exposed to two languages at the same time,so there could be at least two labels for the same referent.Hence bilingual children may be confused and encounter difficulties in learning words,which will slower their word learning process.This paper tries to,based on earlier research,probe into the question that how bilingual children acquire words without the help of ME,and explore whether there are advantages of not using ME in word learning for bilingual children.
基金supported by the MOE Project of the Center for Linguistics and Applied Linguistics,Guangdong University of Foreign Studies,Chinasupported by China's Educational Ministry humanity social science key research center project(No.12JJD740006)
文摘The word processing depth hypothesis implies a positive association between learners＇ word processing and their lexical learning. In research, learners＇ task-inherent involvement load （i.e., word processing） has not been found to be consistently associated with their lexical learning. Meanwhile, existing studies have not obtained consensus results, either, from directly associating learners＇ actual word processing and their lexical learning. Against this backdrop, this paper reports a study investigating the association between Chinese EFL learners＇ actual word processing and their lexical learning in performing a collaborative oral output task. Interactional and statistical analyses revealed that the participants engaged in four types of word processing; their overall word processing was significantly correlated with both their productive and receptive word acquisition and retention; their different types of word processing were significantly correlated with their productive word learning, but showed variances in correlations with their receptive word learning. The findings were discussed from the perspectives of word processing in collaborative output, word processing and lexical learning, and word processing and different modes of lexical learning.
基金supported by the National HighTech Research and Development(863)Program(No.2015AA015401)the National Natural Science Foundation of China(Nos.61533018 and 61402220)+2 种基金the State Scholarship Fund of CSC(No.201608430240)the Philosophy and Social Science Foundation of Hunan Province(No.16YBA323)the Scientific Research Fund of Hunan Provincial Education Department(Nos.16C1378 and 14B153)
文摘Word embedding has drawn a lot of attention due to its usefulness in many NLP tasks. So far a handful of neural-network based word embedding algorithms have been proposed without considering the effects of pronouns in the training corpus. In this paper, we propose using co-reference resolution to improve the word embedding by extracting better context. We evaluate four word embeddings with considerations of co-reference resolution and compare the quality of word embedding on the task of word analogy and word similarity on multiple data sets.Experiments show that by using co-reference resolution, the word embedding performance in the word analogy task can be improved by around 1.88%. We find that the words that are names of countries are affected the most,which is as expected.
