A key goal of knowledge management(KM)is to foster innovation through the ceation of new knowledge.Surprisingly,there is little research on KM in the context of entrepre-neurship,a domain where innovation is considere...A key goal of knowledge management(KM)is to foster innovation through the ceation of new knowledge.Surprisingly,there is little research on KM in the context of entrepre-neurship,a domain where innovation is considered essential.This paper extends estab-lished theories and frameworks for KM to the understudied context of KM in small and medium entrepreneurial firms,particularly young startups.Translating KM fr ameworks,such as the widely studied SECI model,into the entrepreneurial domain could eventually help startups in their quest for sustainability and growth.The SECI model is an aspir ational process with which to build new knowledge,including the explicit knowledge assets that startups commonly lack.However,an aspiration is only useful if the subject knows where he or she stands in relation to it.This study focuses on understanding whether entre-preneurial activities embed into,and can further enable,the"virtuous"knowledge-creation cycle.The secondary objective of this paper is to acknowledge Ikujiro Nonaka's contribution to western and eastern KM theories,and extend his seminal theories into other domains,such as small and medium enterprises.This work pilots the use of a content analysis technique largely used in psychology to analyze the connection between entrepreneurship and KM.With this method,the study highlights how the four phases of the SECI model apply to startup firms in a business incubator in the United States.It provides insights into the knowledge-creation process of entrepreneurs,and suggests how entrepreneurs can improve startup survival through greater awareness and use of KM in their business planning and operational activities.展开更多
Relation Extraction(RE)is to obtain a predefined relation type of two entities mentioned in a piece of text,e.g.,a sentence-level or a document-level text.Most existing studies suffer from the noise in the text,and ne...Relation Extraction(RE)is to obtain a predefined relation type of two entities mentioned in a piece of text,e.g.,a sentence-level or a document-level text.Most existing studies suffer from the noise in the text,and necessary pruning is of great importance.The conventional sentence-level RE task addresses this issue by a denoising method using the shortest dependency path to build a long-range semantic dependency between entity pairs.However,this kind of denoising method is scarce in document-level RE.In this work,we explicitly model a denoised document-level graph based on linguistic knowledge to capture various long-range semantic dependencies among entities.We first formalize a Syntactic Dependency Tree forest(SDT-forest)by introducing the syntax and discourse dependency relation.Then,the Steiner tree algorithm extracts a mention-level denoised graph,Steiner Graph(SG),removing linguistically irrelevant words from the SDT-forest.We then devise a slide residual attention to highlight word-level evidence on text and SG.Finally,the classification is established on the SG to infer the relations of entity pairs.We conduct extensive experiments on three public datasets.The results evidence that our method is beneficial to establish long-range semantic dependency and can improve the classification performance with longer texts.展开更多
This study investigates the cognitive and metacognitive processes used by EFL test-takers in completing a compound dictation test through analyses of their verbal protocols obtained immediately after the test and thro...This study investigates the cognitive and metacognitive processes used by EFL test-takers in completing a compound dictation test through analyses of their verbal protocols obtained immediately after the test and through semi-structured retrospective interviews. The study explores relationships between the test-takers＇ actual performance and the instructions for the compound dictation test, the language abilities measured, any major construct-irrelevant factors affecting the test-taking processes, and the performance patterns of performance across test-takers of different overall proficiency levels. Findings are as follows. （1） Test-takers＇ actual performance does not apparently relate to the instructions given in the compound dictation test, which may raise doubts over the effectiveness of the instructions, thereby posing a potential threat to test validity. （2） Test-takers may pay more attention to the pronunciation of the words to be used to fill the blanks than to the actual meaning of the words, their difficulties in spelling and sentential expression possibly interfering with test performance even though they appear to use a variety of cognitive and metacognitive strategies throughout the test. （3） A number of construct-irrelevant factors posing a potential threat to test validity were found in the test-taking processes. Some of these factors are related to the test-takers, for example, memory capacity, attention failure and psychological factors, while others relate to the test, including speech rate and time constraints. （4） Test-takers in the study at all three proficiency levels appeared not to follow the instructions given in the compound dictation test. However, higher proficiency test-takers appeared to make more frequent use of cognitive and metacognitive strategies, and they appeared to be less influenced by construct-irrelevant factors.展开更多
文摘A key goal of knowledge management(KM)is to foster innovation through the ceation of new knowledge.Surprisingly,there is little research on KM in the context of entrepre-neurship,a domain where innovation is considered essential.This paper extends estab-lished theories and frameworks for KM to the understudied context of KM in small and medium entrepreneurial firms,particularly young startups.Translating KM fr ameworks,such as the widely studied SECI model,into the entrepreneurial domain could eventually help startups in their quest for sustainability and growth.The SECI model is an aspir ational process with which to build new knowledge,including the explicit knowledge assets that startups commonly lack.However,an aspiration is only useful if the subject knows where he or she stands in relation to it.This study focuses on understanding whether entre-preneurial activities embed into,and can further enable,the"virtuous"knowledge-creation cycle.The secondary objective of this paper is to acknowledge Ikujiro Nonaka's contribution to western and eastern KM theories,and extend his seminal theories into other domains,such as small and medium enterprises.This work pilots the use of a content analysis technique largely used in psychology to analyze the connection between entrepreneurship and KM.With this method,the study highlights how the four phases of the SECI model apply to startup firms in a business incubator in the United States.It provides insights into the knowledge-creation process of entrepreneurs,and suggests how entrepreneurs can improve startup survival through greater awareness and use of KM in their business planning and operational activities.
基金supported by the National Natural Science Foundation of China(Nos.U19A2059&62176046).
文摘Relation Extraction(RE)is to obtain a predefined relation type of two entities mentioned in a piece of text,e.g.,a sentence-level or a document-level text.Most existing studies suffer from the noise in the text,and necessary pruning is of great importance.The conventional sentence-level RE task addresses this issue by a denoising method using the shortest dependency path to build a long-range semantic dependency between entity pairs.However,this kind of denoising method is scarce in document-level RE.In this work,we explicitly model a denoised document-level graph based on linguistic knowledge to capture various long-range semantic dependencies among entities.We first formalize a Syntactic Dependency Tree forest(SDT-forest)by introducing the syntax and discourse dependency relation.Then,the Steiner tree algorithm extracts a mention-level denoised graph,Steiner Graph(SG),removing linguistically irrelevant words from the SDT-forest.We then devise a slide residual attention to highlight word-level evidence on text and SG.Finally,the classification is established on the SG to infer the relations of entity pairs.We conduct extensive experiments on three public datasets.The results evidence that our method is beneficial to establish long-range semantic dependency and can improve the classification performance with longer texts.
基金part of the achievements funded by the Fundamental Research Funds for the Central Universities in China (No. 0205005201030)the National Scholarship Council of China (No. 2010850066)granted to the first author to support a one-year visiting professorship
文摘This study investigates the cognitive and metacognitive processes used by EFL test-takers in completing a compound dictation test through analyses of their verbal protocols obtained immediately after the test and through semi-structured retrospective interviews. The study explores relationships between the test-takers＇ actual performance and the instructions for the compound dictation test, the language abilities measured, any major construct-irrelevant factors affecting the test-taking processes, and the performance patterns of performance across test-takers of different overall proficiency levels. Findings are as follows. （1） Test-takers＇ actual performance does not apparently relate to the instructions given in the compound dictation test, which may raise doubts over the effectiveness of the instructions, thereby posing a potential threat to test validity. （2） Test-takers may pay more attention to the pronunciation of the words to be used to fill the blanks than to the actual meaning of the words, their difficulties in spelling and sentential expression possibly interfering with test performance even though they appear to use a variety of cognitive and metacognitive strategies throughout the test. （3） A number of construct-irrelevant factors posing a potential threat to test validity were found in the test-taking processes. Some of these factors are related to the test-takers, for example, memory capacity, attention failure and psychological factors, while others relate to the test, including speech rate and time constraints. （4） Test-takers in the study at all three proficiency levels appeared not to follow the instructions given in the compound dictation test. However, higher proficiency test-takers appeared to make more frequent use of cognitive and metacognitive strategies, and they appeared to be less influenced by construct-irrelevant factors.
