Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related...Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy(metabolically healthy obese, MHO), so which fat deposition(subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers(ORCs) share a molecular signature? Are there common(overlapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse efect of obesity on human condition.展开更多
Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the eve...Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.展开更多
Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding appro...Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding approaches are deficient in representing some complex relations,resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.Methods To this end,we propose MKEAH:Multimodal Knowledge Extraction and Accumulation on Hyperplanes.To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information,two losses are proposed to learn the triplet representations from the complementary views:range loss and orthogonal loss.To interpret the capability of extracting topic-related knowledge,we present the Topic Similarity(TS)between topic and entity-relations.Results Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering.Our model outperformed state-of-the-art methods by 2.12%and 3.24%on two challenging knowledge-request datasets:OK-VQA and KRVQA,respectively.Conclusions The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.展开更多
Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems.However,with the constant evolution of algorithms,data,and computing power,the ...Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems.However,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced efficiency.This study aims to minimize the inference time of such models while maintaining computational performance.It also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and DPAL-BERTC.This research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge transfer.The experimental results showed that the distilled models greatly outperform models trained from scratch.In addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the original.This demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.展开更多
How to Differentiate and Treat Bi-syndrome by Acupuncture and Moxibustion?Bi-syndrome is the syndrome due to invasion of the exogenous pathogenic factors of wind, cold and dampness, which obstruct the channels and col...How to Differentiate and Treat Bi-syndrome by Acupuncture and Moxibustion?Bi-syndrome is the syndrome due to invasion of the exogenous pathogenic factors of wind, cold and dampness, which obstruct the channels and collaterals, leading to stagnated flow of qi and blood, characterized by such clinical manifestations as aching pain, numbness, heaviness, limited flexion and extension of the muscles, tendons and joints, or swelling and burning heat of the joints. This syndrome includes rheumatic arthritis, rheumatoid arthritis, osseous arthritis, and various neuralgia. The endogenous causative factors for the occurrence of Bi-syndrome are insufficiency of yang-qi, essence and blood, while the exogenous causative factors are the pathogenic wind, cold, and dampness. At the initial stage of the disease, the excessiveness of pathogen usually prevails, and the disease tends to be located in the limbs, skin and muscles, and channels and collaterals; while at the chronic stage, there often exists deficiency of the vital-qi or deficiency and excess intermixed, and the disease tends to be located deeper in the tendons and bones or in the zang-fu organs.展开更多
Teachers’ questions have been regarded as an important component in foreign language teaching context. The present paper aims to present a brief investigation into teachers’ question types and students’ answers in ...Teachers’ questions have been regarded as an important component in foreign language teaching context. The present paper aims to present a brief investigation into teachers’ question types and students’ answers in primary school English teaching, and tries to draw some implications for primary school English teachers. The video was transcribed and analyzed by the researcher. According to what is surveyed in the study, some questioning strategies were put forward for primary English teaching in the future.展开更多
On June 3 1996, Minister of Electric Power Shi Dazhen accepted news-covering of Britain "Financial Times" resident reporter in Beijing Tony Walker, resident reporter in Hong Kong John Ridding and Asian Edito...On June 3 1996, Minister of Electric Power Shi Dazhen accepted news-covering of Britain "Financial Times" resident reporter in Beijing Tony Walker, resident reporter in Hong Kong John Ridding and Asian Editor Peter Montagnon, and answered their questions in the aspects of the 9th Five-year Development Planning of China’s Electric Power and some related issues.展开更多
1.Harry’s mom has three boys.The first boy’s name is Tom.the second boy’s named is David.What is the third boy’s name?2.How can you make a fire with two sticks?3.A boy fell off a 100-foot ladder and did not get hu...1.Harry’s mom has three boys.The first boy’s name is Tom.the second boy’s named is David.What is the third boy’s name?2.How can you make a fire with two sticks?3.A boy fell off a 100-foot ladder and did not get hurt.How can this be?4.I’m full when I am gone.and I’m empty when I am here.What am I?5.What kind of key can not open doors?展开更多
Based on personal observation and students’ self-reports, this article studies the characteristics presented by students in answering questions. It is found that Chinese culture plays an important part in explaining ...Based on personal observation and students’ self-reports, this article studies the characteristics presented by students in answering questions. It is found that Chinese culture plays an important part in explaining their specific behaviors. Hence, in order to lessen the negative effect of it, the author offers her own suggestions.展开更多
With the emergence of large-scale knowledge base,how to use triple information to generate natural questions is a key technology in question answering systems.The traditional way of generating questions require a lot ...With the emergence of large-scale knowledge base,how to use triple information to generate natural questions is a key technology in question answering systems.The traditional way of generating questions require a lot of manual intervention and produce lots of noise.To solve these problems,we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions.The semi-automated model can generate question templates and real questions combining the knowledge base and center graph.The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network.Meanwhile,the attention mechanism is utilized in the decoding layer,which makes the triples and generated questions more relevant.Finally,the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.展开更多
Fatigue is best defined as difficulty in initiating or sustaining voluntary activities, and is thought to be accompanied by deterioration of performance. Fatigue can be caused by many factors such as physical and ment...Fatigue is best defined as difficulty in initiating or sustaining voluntary activities, and is thought to be accompanied by deterioration of performance. Fatigue can be caused by many factors such as physical and mental stress, disturbance in the circadian rhythm, and various diseases. For example, following the flu or other types of infections, everyone has experienced a sense of fatigue that can last for days or weeks. The fatigue sensation is thought to be one of the signals for the body to suppress physical activity in order to regain health. The mechanism of induction of the fatigue sensation following viral infection has not been well understood. Although fatigue was once thought to be caused by fever, our recent study with an animal model of viral infection demonstrated that the fatigue sensation is caused not by fever, but rather,展开更多
Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to i...Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to investigate the critical factors which influence users' intention to continue contributing knowledge in the SQA community.Design/methodology/approach:Grounded on information systems(IS) continuance theory,this study put forward a model of the factors that influence SQA community members' intention to continue contributing knowledge.Survey was conducted to gather data from knowledge contributors of four major Chinese SQA communities(Baidu Knows,Sina iAsk,Soso Ask and Yahoo! Knowledge).By using the partial least squares(PLS) technique,research hypotheses derived from the proposed model were empirically validated.Findings:Except enjoyment in helping others and knowledge self-efficacy,all other factors including extrinsic reward,reputation enhancement,realization of self-worth,perceived usefulness,attitude towards knowledge contribution,and satisfaction exert significant impacts on users' continuance intentions in an SQA community.Research limitations:First,important factors such as the ease of use of information systems which may influence users' continuance intentions were not investigated in the study.Second,the study sample needs to be enlarged,and users of smaller SQA communities should also be included,to make the results more representative.Practical implications:This study will help SQA community designers and managers develop or improve incentive mechanisms to attract more people to contribute their knowledge and promote the development of the SQA community.Originality/value:This study improves the previous research models and puts forward a model of user continuance intention to contribute knowledge in an SQA community.It will extend the understanding of SQA community users' intention to continue contributing knowledge by distinguishing these users' different roles and focusing only on knowledge contributors.展开更多
In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant attention.However,as algorithms,data,and comput...In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant attention.However,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has surfaced.Consequently,model training has become more costly and less efficient.To enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language model.Firstly,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is formed.Then,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the performance.Finally,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training efficiency.Compared with traditional models,PAL-BERT significantly improves the NLP task’s performance.展开更多
The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challen...The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.展开更多
Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of ...Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of knowledge base and corpus,the Word Segmentation and POS Tagging of text,the Grammatical Analysis and Semantic Analysis of sentences etc.This thesis dissertated mainly the denotation of knowledge-information based on semantic network in QAS,the stochastic syntax-parse model named LSF of knowledge-information in QAS,the structure and constitution of QAS.And the LSF model's parameters were exercised,which proved that they were feasible.At the same time,through "the limited-domain QAS" which was exploited for banks by us,these technologies were proved effective and propagable.展开更多
文摘Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy(metabolically healthy obese, MHO), so which fat deposition(subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers(ORCs) share a molecular signature? Are there common(overlapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse efect of obesity on human condition.
文摘Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.
基金Supported by National Nature Science Foudation of China(61976160,61906137,61976158,62076184,62076182)Shanghai Science and Technology Plan Project(21DZ1204800)。
文摘Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding approaches are deficient in representing some complex relations,resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.Methods To this end,we propose MKEAH:Multimodal Knowledge Extraction and Accumulation on Hyperplanes.To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information,two losses are proposed to learn the triplet representations from the complementary views:range loss and orthogonal loss.To interpret the capability of extracting topic-related knowledge,we present the Topic Similarity(TS)between topic and entity-relations.Results Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering.Our model outperformed state-of-the-art methods by 2.12%and 3.24%on two challenging knowledge-request datasets:OK-VQA and KRVQA,respectively.Conclusions The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.
基金supported by Sichuan Science and Technology Program(2023YFSY0026,2023YFH0004).
文摘Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems.However,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced efficiency.This study aims to minimize the inference time of such models while maintaining computational performance.It also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and DPAL-BERTC.This research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge transfer.The experimental results showed that the distilled models greatly outperform models trained from scratch.In addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the original.This demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.
文摘How to Differentiate and Treat Bi-syndrome by Acupuncture and Moxibustion?Bi-syndrome is the syndrome due to invasion of the exogenous pathogenic factors of wind, cold and dampness, which obstruct the channels and collaterals, leading to stagnated flow of qi and blood, characterized by such clinical manifestations as aching pain, numbness, heaviness, limited flexion and extension of the muscles, tendons and joints, or swelling and burning heat of the joints. This syndrome includes rheumatic arthritis, rheumatoid arthritis, osseous arthritis, and various neuralgia. The endogenous causative factors for the occurrence of Bi-syndrome are insufficiency of yang-qi, essence and blood, while the exogenous causative factors are the pathogenic wind, cold, and dampness. At the initial stage of the disease, the excessiveness of pathogen usually prevails, and the disease tends to be located in the limbs, skin and muscles, and channels and collaterals; while at the chronic stage, there often exists deficiency of the vital-qi or deficiency and excess intermixed, and the disease tends to be located deeper in the tendons and bones or in the zang-fu organs.
文摘Teachers’ questions have been regarded as an important component in foreign language teaching context. The present paper aims to present a brief investigation into teachers’ question types and students’ answers in primary school English teaching, and tries to draw some implications for primary school English teachers. The video was transcribed and analyzed by the researcher. According to what is surveyed in the study, some questioning strategies were put forward for primary English teaching in the future.
文摘On June 3 1996, Minister of Electric Power Shi Dazhen accepted news-covering of Britain "Financial Times" resident reporter in Beijing Tony Walker, resident reporter in Hong Kong John Ridding and Asian Editor Peter Montagnon, and answered their questions in the aspects of the 9th Five-year Development Planning of China’s Electric Power and some related issues.
文摘1.Harry’s mom has three boys.The first boy’s name is Tom.the second boy’s named is David.What is the third boy’s name?2.How can you make a fire with two sticks?3.A boy fell off a 100-foot ladder and did not get hurt.How can this be?4.I’m full when I am gone.and I’m empty when I am here.What am I?5.What kind of key can not open doors?
文摘Based on personal observation and students’ self-reports, this article studies the characteristics presented by students in answering questions. It is found that Chinese culture plays an important part in explaining their specific behaviors. Hence, in order to lessen the negative effect of it, the author offers her own suggestions.
基金supported by National Nature Science Foundation(No.61501529,No.61331013)National Language Committee Project of China(No.ZDI125-36)Young Teachers'Scientific Research Project in Minzu University of China.
文摘With the emergence of large-scale knowledge base,how to use triple information to generate natural questions is a key technology in question answering systems.The traditional way of generating questions require a lot of manual intervention and produce lots of noise.To solve these problems,we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions.The semi-automated model can generate question templates and real questions combining the knowledge base and center graph.The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network.Meanwhile,the attention mechanism is utilized in the decoding layer,which makes the triples and generated questions more relevant.Finally,the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.
基金supported in part by JST,CREST to Y.K.Special Coordination Funds for Promoting Science and Technology from the Ministry of Education,Culture,Sports,Science and Technology of the Japanese Government to Y.K.a Grant-in-Aid for Scientific Research from the Ministry of Education,Culture,Sports,Science and Technology of the Japanese Government to Y.K.(25460399)
文摘Fatigue is best defined as difficulty in initiating or sustaining voluntary activities, and is thought to be accompanied by deterioration of performance. Fatigue can be caused by many factors such as physical and mental stress, disturbance in the circadian rhythm, and various diseases. For example, following the flu or other types of infections, everyone has experienced a sense of fatigue that can last for days or weeks. The fatigue sensation is thought to be one of the signals for the body to suppress physical activity in order to regain health. The mechanism of induction of the fatigue sensation following viral infection has not been well understood. Although fatigue was once thought to be caused by fever, our recent study with an animal model of viral infection demonstrated that the fatigue sensation is caused not by fever, but rather,
基金supported by Wuhan University Development Program for Researchers Born after the 1970s
文摘Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to investigate the critical factors which influence users' intention to continue contributing knowledge in the SQA community.Design/methodology/approach:Grounded on information systems(IS) continuance theory,this study put forward a model of the factors that influence SQA community members' intention to continue contributing knowledge.Survey was conducted to gather data from knowledge contributors of four major Chinese SQA communities(Baidu Knows,Sina iAsk,Soso Ask and Yahoo! Knowledge).By using the partial least squares(PLS) technique,research hypotheses derived from the proposed model were empirically validated.Findings:Except enjoyment in helping others and knowledge self-efficacy,all other factors including extrinsic reward,reputation enhancement,realization of self-worth,perceived usefulness,attitude towards knowledge contribution,and satisfaction exert significant impacts on users' continuance intentions in an SQA community.Research limitations:First,important factors such as the ease of use of information systems which may influence users' continuance intentions were not investigated in the study.Second,the study sample needs to be enlarged,and users of smaller SQA communities should also be included,to make the results more representative.Practical implications:This study will help SQA community designers and managers develop or improve incentive mechanisms to attract more people to contribute their knowledge and promote the development of the SQA community.Originality/value:This study improves the previous research models and puts forward a model of user continuance intention to contribute knowledge in an SQA community.It will extend the understanding of SQA community users' intention to continue contributing knowledge by distinguishing these users' different roles and focusing only on knowledge contributors.
基金Supported by Sichuan Science and Technology Program(2021YFQ0003,2023YFSY0026,2023YFH0004).
文摘In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant attention.However,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has surfaced.Consequently,model training has become more costly and less efficient.To enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language model.Firstly,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is formed.Then,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the performance.Finally,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training efficiency.Compared with traditional models,PAL-BERT significantly improves the NLP task’s performance.
文摘The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60305009)the Ph.D Degree Teacher Foundation of North China Electric Power University(Grant No.H0585).
文摘Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of knowledge base and corpus,the Word Segmentation and POS Tagging of text,the Grammatical Analysis and Semantic Analysis of sentences etc.This thesis dissertated mainly the denotation of knowledge-information based on semantic network in QAS,the stochastic syntax-parse model named LSF of knowledge-information in QAS,the structure and constitution of QAS.And the LSF model's parameters were exercised,which proved that they were feasible.At the same time,through "the limited-domain QAS" which was exploited for banks by us,these technologies were proved effective and propagable.
