Sentiment analysis is a fine‐grained analysis task that aims to identify the sentiment polarity of a specified sentence.Existing methods in Chinese sentiment analysis tasks only consider sentiment features from a sin...Sentiment analysis is a fine‐grained analysis task that aims to identify the sentiment polarity of a specified sentence.Existing methods in Chinese sentiment analysis tasks only consider sentiment features from a single pole and scale and thus cannot fully exploit and utilise sentiment feature information,making their performance less than ideal.To resolve the problem,the authors propose a new method,GP‐FMLNet,that integrates both glyph and phonetic information and design a novel feature matrix learning process for phonetic features with which to model words that have the same pinyin information but different glyph information.Our method solves the problem of misspelling words influencing sentiment polarity prediction results.Specifically,the authors iteratively mine character,glyph,and pinyin features from the input comments sentences.Then,the authors use soft attention and matrix compound modules to model the phonetic features,which empowers their model to keep on zeroing in on the dynamic‐setting words in various positions and to dispense with the impacts of the deceptive‐setting ones.Ex-periments on six public datasets prove that the proposed model fully utilises the glyph and phonetic information and improves on the performance of existing Chinese senti-ment analysis algorithms.展开更多
In this paper,conjugate k-holomorphic functions and generalized k-holomorphic functions are defined in the two-dimensional complex space,and the corresponding Riemann boundary value problems and the inverse problems a...In this paper,conjugate k-holomorphic functions and generalized k-holomorphic functions are defined in the two-dimensional complex space,and the corresponding Riemann boundary value problems and the inverse problems are discussed on generalized bicylinders.By the characteristics of the corresponding functions and boundary properties of the Cauchy type singular integral operators with conjugate k-holomorphic kernels,the general solutions and special solutions of the corresponding boundary value problems are studied in a detailed fashion,and the integral expressions of the solutions are obtained.展开更多
k holomorphic functions are a type of generation of holomorphic functions.In this paper,a nonlinear boundary value problem for k holomorphic functions is primarily discussed on generalized polycylinders in C^(2).The e...k holomorphic functions are a type of generation of holomorphic functions.In this paper,a nonlinear boundary value problem for k holomorphic functions is primarily discussed on generalized polycylinders in C^(2).The existence of the solution for the problem is studied in detail with the help of the boundary properties of Cauchy type singular integral operators with a k holomorphic kernel.Furthermore,the integral representation for the solution is obtained.展开更多
Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine(TCM).We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automa...Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine(TCM).We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automated diagnosis in TCM.We analyze the reasoning path patterns from symptom to syndromes on the knowledge graph.There are two kinds of path patterns in the knowledge graph:one-hop and two-hop.The one-hop path pattern maps the symptom to syndromes immediately.The two-hop path pattern maps the symptom to syndromes through the nature of disease,etiology,and pathomechanism to support the diagnostic reasoning.Considering the different support strengths for the knowledge paths in reasoning,we design a dynamic weight mechanism.We utilize Naïve Bayes and TF-IDF to implement the reasoning method and the weighted score calculation.The proposed method reasons the syndrome results by calculating the possibility according to the weighted score of the path in the knowledge graph based on the reasoning path patterns.We evaluate the method with clinical records and clinical practice in hospitals.The preliminary results suggest that the method achieves high performance and can help TCM doctors make better diagnosis decisions in practice.Meanwhile,the method is robust and explainable under the guide of the knowledge graph.It could help TCM physicians,especially primary physicians in rural areas,and provide clinical decision support in clinical practice.展开更多
As one of the most valuable assets in China,traditional medicine has a long history and contains pieces of knowledge.The diagnosis and treatment of Traditional Chinese Medicine(TCM)has benefited from the natural langu...As one of the most valuable assets in China,traditional medicine has a long history and contains pieces of knowledge.The diagnosis and treatment of Traditional Chinese Medicine(TCM)has benefited from the natural language processing technology.This paper proposes a knowledge-based syndrome reasoning method in computer-assisted diagnosis.This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path.According to this reasoning path,we could infer the path from the symptoms to the syndrome and get all possibilities via the relationship between symptoms and causes.Moreover,this study applies the Term Frequency-Inverse Document Frequency(TF-IDF)idea to the computer-assisted diagnosis of TCM for the score of syndrome calculation.Finally,combined with symptoms,syndrome,and causes,the disease could be confirmed comprehensively by voting,and the experiment shows that the system can help doctors and families to disease diagnosis effectively.展开更多
In recent years,there are some problems in science and technology management,such as untimely task supervision and independent information system,which makes it difficult to achieve accurate,quantitative and standardi...In recent years,there are some problems in science and technology management,such as untimely task supervision and independent information system,which makes it difficult to achieve accurate,quantitative and standardized management.The storage of scientific research test data is scattered,and there are many deficiencies in the management,promotion and use of existing intellectual property.In this paper,on the basis of the knowledge economy,intelligence economy under the conditions of knowledge management concept and cutting-edge technology,technology management and service management related data,information,knowledge,method of blend together.Based on science and technology management,knowledge management as the core of management and service platform of science and technology technical route,main function,construction principles and standards.In order to realize the management systematization of science and technology,intelligent,better educated,multi-level and multi-angle application services.展开更多
With the success of new speech-based human-computer interfaces,there is a great need for effective and friendly dialogue agents that can communicate with people naturally and continuously.However,the lack of personali...With the success of new speech-based human-computer interfaces,there is a great need for effective and friendly dialogue agents that can communicate with people naturally and continuously.However,the lack of personality and consistency is one of critical problems in neural dialogue systems.In this paper,we aim to generate consistent response with fixed profile and background information for building a realistic dialogue system.Based on the encoder-decoder model,we propose a retrieval mechanism to deliver natural and fluent response with proper information from a profile database.Moreover,in order to improve the efficiency of training the dataset related to profile information,we adopt a method of pre-training and adjustment for general dataset and profile dataset.Our model is trained by social dialogue data from Weibo.According to both automatic and human evaluation metrics,the proposed model significantly outperforms standard encoder-decoder model and other improved models on providing the correct profile and high-quality responses.展开更多
Herbaceous marsh is the most widely distributed type of marsh wetland ecosystem,and has important ecological functions such as water conservation,climate regulation,carbon storage and fixation,and sheltering rare spec...Herbaceous marsh is the most widely distributed type of marsh wetland ecosystem,and has important ecological functions such as water conservation,climate regulation,carbon storage and fixation,and sheltering rare species.The carbon sequestration function of herbaceous marsh plays a key role in slowing climate warming and maintaining regional environmental stability.Vegetation biomass is an important index reflecting the carbon sequestration capacity of wetlands.Investigating the biomass of marsh vegetation can provide a scientific basis for estimating the carbon storage and carbon sequestration capacity of marshes.Based on field survey data of aboveground biomass of herbaceous marsh vegetation and the distribution data set of marsh in China,we analyzed the aboveground biomass and its spatial distribution pattern of herbaceous marsh on a national scale for the first time.The results showed that in China the total area of herbaceous marsh was 9.7×10^(4) km^(2),the average density of aboveground biomass of herbaceous marsh vegetation was 227.5±23.0 g C m-2(95%confidence interval,the same below),and the total aboveground biomass was 22.2±2.2 Tg C(1 Tg=1012 g).The aboveground biomass density of herbaceous marsh vegetation is generally low in Northeast China and the Tibetan Plateau,and high in central North China and coastal regions in China.In different marsh distribution regions of China,the average biomass density of herbaceous marsh vegetation from small to large was as follows:temperate humid and semi-humid marsh region(182.3±49.3 g C m^(-2))<Tibetan Plateau marsh region(243.9±26.6 g C m-2)<temperate arid and semi-arid marsh region(300.5±73.2 g C m-2)<subtropical humid marsh region(348.4±59.0 g C m-2)<coastal marsh region(675.4±73.8 g C m-2). Due to the different area of herbaceous marsh, the total aboveground biomass of herbaceous marsh vegetation in different marsh distribution regions was the largest in the temperate humid and semi-humid marsh region(9.6±2.6 Tg C), and was the smallest in the coastal marsh region(1.1±0.1 Tg C). The spatial distribution of aboveground biomass of herbaceous marsh vegetation in China has obvious non-zonality characteristics, but also presents certain zonality in some regions. The aboveground biomass of herbaceous marsh vegetation in the Tibetan Plateau decreased with the increase of altitude. With the aggravation of drought, the aboveground biomass of herbaceous marsh vegetation in temperate humid and semi-humid regions and temperate arid and semi-arid regions decreased first and then did not obviously change. The aboveground biomass of herbaceous marsh vegetation in temperate humid and semi-humid regions was relatively larger in the regions with higher average annual temperature. The results can provide scientific basis for accurately evaluating the adjustment action of wetland ecosystems on climate, and provide decision support for adaptive management of wetland ecosystems.展开更多
Boolean functions used in a cryptographic system should have high algebraic immunity to resist algebraic attacks. This paper presents a matrix method for constructing balanced Boolean functions achieving maximum algeb...Boolean functions used in a cryptographic system should have high algebraic immunity to resist algebraic attacks. This paper presents a matrix method for constructing balanced Boolean functions achieving maximum algebraic immunity.展开更多
In this paper, we study the skyline group problem over a data stream. An object can dominate another object if it is not worse than the other object on all attributes and is better than the other object on at least on...In this paper, we study the skyline group problem over a data stream. An object can dominate another object if it is not worse than the other object on all attributes and is better than the other object on at least one attribute. If an object cannot be dominated by any other object, it is a skyline object. The skyline group problem involves finding k-item groups that cannot be dominated by any other k-item group. Existing algorithms designed to find skyline groups can only process static data. However, data changes as a stream with time in many applications,and algorithms should be designed to support skyline group queries on dynamic data. In this paper, we propose new algorithms to find skyline groups over a data stream. We use data structures, namely a hash table, dominance graph, and matrix, to store dominance information and update results incrementally. We conduct experiments on synthetic datasets to evaluate the performance of the proposed algorithms. The experimental results show that our algorithms can efficiently find skyline groups over a data stream.展开更多
Almansi-type decomposition theorem for bi-k-regular functions defined in a star-like domainΩ⊆R^(n+1)×R^(n+1)centered at the origin with values in the Clifford algebra Cl_(2n+2,0)(R)is proved.As a corollary,Alman...Almansi-type decomposition theorem for bi-k-regular functions defined in a star-like domainΩ⊆R^(n+1)×R^(n+1)centered at the origin with values in the Clifford algebra Cl_(2n+2,0)(R)is proved.As a corollary,Almansi-type decomposition theorem for biharmonic functions of degree k is given.展开更多
基金Science and Technology Innovation 2030‐“New Generation Artificial Intelligence”major project,Grant/Award Number:2020AAA0108703。
文摘Sentiment analysis is a fine‐grained analysis task that aims to identify the sentiment polarity of a specified sentence.Existing methods in Chinese sentiment analysis tasks only consider sentiment features from a single pole and scale and thus cannot fully exploit and utilise sentiment feature information,making their performance less than ideal.To resolve the problem,the authors propose a new method,GP‐FMLNet,that integrates both glyph and phonetic information and design a novel feature matrix learning process for phonetic features with which to model words that have the same pinyin information but different glyph information.Our method solves the problem of misspelling words influencing sentiment polarity prediction results.Specifically,the authors iteratively mine character,glyph,and pinyin features from the input comments sentences.Then,the authors use soft attention and matrix compound modules to model the phonetic features,which empowers their model to keep on zeroing in on the dynamic‐setting words in various positions and to dispense with the impacts of the deceptive‐setting ones.Ex-periments on six public datasets prove that the proposed model fully utilises the glyph and phonetic information and improves on the performance of existing Chinese senti-ment analysis algorithms.
基金supported by the NSF of Henan Province(222300420397,242300421394)Xie’s research was supported by the NSFC(11571089,11871191).
文摘In this paper,conjugate k-holomorphic functions and generalized k-holomorphic functions are defined in the two-dimensional complex space,and the corresponding Riemann boundary value problems and the inverse problems are discussed on generalized bicylinders.By the characteristics of the corresponding functions and boundary properties of the Cauchy type singular integral operators with conjugate k-holomorphic kernels,the general solutions and special solutions of the corresponding boundary value problems are studied in a detailed fashion,and the integral expressions of the solutions are obtained.
基金the NSF of China(11571089,11871191)the NSF of Henan Province(222300420397)+1 种基金the NSF of Hebei Province(A2022208007)the Key Foundation of Hebei Normal University(L2018Z01)。
文摘k holomorphic functions are a type of generation of holomorphic functions.In this paper,a nonlinear boundary value problem for k holomorphic functions is primarily discussed on generalized polycylinders in C^(2).The existence of the solution for the problem is studied in detail with the help of the boundary properties of Cauchy type singular integral operators with a k holomorphic kernel.Furthermore,the integral representation for the solution is obtained.
基金This work is supported by the National Key Research and Development Program of China under Grant 2017YFB1002304the China Scholarship Council under Grant 201906465021.
文摘Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine(TCM).We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automated diagnosis in TCM.We analyze the reasoning path patterns from symptom to syndromes on the knowledge graph.There are two kinds of path patterns in the knowledge graph:one-hop and two-hop.The one-hop path pattern maps the symptom to syndromes immediately.The two-hop path pattern maps the symptom to syndromes through the nature of disease,etiology,and pathomechanism to support the diagnostic reasoning.Considering the different support strengths for the knowledge paths in reasoning,we design a dynamic weight mechanism.We utilize Naïve Bayes and TF-IDF to implement the reasoning method and the weighted score calculation.The proposed method reasons the syndrome results by calculating the possibility according to the weighted score of the path in the knowledge graph based on the reasoning path patterns.We evaluate the method with clinical records and clinical practice in hospitals.The preliminary results suggest that the method achieves high performance and can help TCM doctors make better diagnosis decisions in practice.Meanwhile,the method is robust and explainable under the guide of the knowledge graph.It could help TCM physicians,especially primary physicians in rural areas,and provide clinical decision support in clinical practice.
基金Supported by the National Key Research and Development Program of China under Grant 2017YFB1002304 and the National Natural Science Foundation of China(No.61672178)The author who received the grant is Azguri,and the official website of the funder is http://www.most.gov.cn/.
文摘As one of the most valuable assets in China,traditional medicine has a long history and contains pieces of knowledge.The diagnosis and treatment of Traditional Chinese Medicine(TCM)has benefited from the natural language processing technology.This paper proposes a knowledge-based syndrome reasoning method in computer-assisted diagnosis.This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path.According to this reasoning path,we could infer the path from the symptoms to the syndrome and get all possibilities via the relationship between symptoms and causes.Moreover,this study applies the Term Frequency-Inverse Document Frequency(TF-IDF)idea to the computer-assisted diagnosis of TCM for the score of syndrome calculation.Finally,combined with symptoms,syndrome,and causes,the disease could be confirmed comprehensively by voting,and the experiment shows that the system can help doctors and families to disease diagnosis effectively.
基金supported by Research on Construction of Green Building Material Information Management Platform(Grant 2016024).
文摘In recent years,there are some problems in science and technology management,such as untimely task supervision and independent information system,which makes it difficult to achieve accurate,quantitative and standardized management.The storage of scientific research test data is scattered,and there are many deficiencies in the management,promotion and use of existing intellectual property.In this paper,on the basis of the knowledge economy,intelligence economy under the conditions of knowledge management concept and cutting-edge technology,technology management and service management related data,information,knowledge,method of blend together.Based on science and technology management,knowledge management as the core of management and service platform of science and technology technical route,main function,construction principles and standards.In order to realize the management systematization of science and technology,intelligent,better educated,multi-level and multi-angle application services.
基金This work is supported by the National Key Research and Development Program of China under Grant 2017YFB1002304。
文摘With the success of new speech-based human-computer interfaces,there is a great need for effective and friendly dialogue agents that can communicate with people naturally and continuously.However,the lack of personality and consistency is one of critical problems in neural dialogue systems.In this paper,we aim to generate consistent response with fixed profile and background information for building a realistic dialogue system.Based on the encoder-decoder model,we propose a retrieval mechanism to deliver natural and fluent response with proper information from a profile database.Moreover,in order to improve the efficiency of training the dataset related to profile information,we adopt a method of pre-training and adjustment for general dataset and profile dataset.Our model is trained by social dialogue data from Weibo.According to both automatic and human evaluation metrics,the proposed model significantly outperforms standard encoder-decoder model and other improved models on providing the correct profile and high-quality responses.
基金supported by the National Science&Technology Fundamental Resources Investigation Program of China(Grant No.2013FY111800)the National Natural Science Foundation of China(Grant Nos.41971065 and U19A2042)the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.ZDBS-LY7019),the Youth Innovation Promotion Association,Chinese Academy of Sciences(Grant No.2019235)。
文摘Herbaceous marsh is the most widely distributed type of marsh wetland ecosystem,and has important ecological functions such as water conservation,climate regulation,carbon storage and fixation,and sheltering rare species.The carbon sequestration function of herbaceous marsh plays a key role in slowing climate warming and maintaining regional environmental stability.Vegetation biomass is an important index reflecting the carbon sequestration capacity of wetlands.Investigating the biomass of marsh vegetation can provide a scientific basis for estimating the carbon storage and carbon sequestration capacity of marshes.Based on field survey data of aboveground biomass of herbaceous marsh vegetation and the distribution data set of marsh in China,we analyzed the aboveground biomass and its spatial distribution pattern of herbaceous marsh on a national scale for the first time.The results showed that in China the total area of herbaceous marsh was 9.7×10^(4) km^(2),the average density of aboveground biomass of herbaceous marsh vegetation was 227.5±23.0 g C m-2(95%confidence interval,the same below),and the total aboveground biomass was 22.2±2.2 Tg C(1 Tg=1012 g).The aboveground biomass density of herbaceous marsh vegetation is generally low in Northeast China and the Tibetan Plateau,and high in central North China and coastal regions in China.In different marsh distribution regions of China,the average biomass density of herbaceous marsh vegetation from small to large was as follows:temperate humid and semi-humid marsh region(182.3±49.3 g C m^(-2))<Tibetan Plateau marsh region(243.9±26.6 g C m-2)<temperate arid and semi-arid marsh region(300.5±73.2 g C m-2)<subtropical humid marsh region(348.4±59.0 g C m-2)<coastal marsh region(675.4±73.8 g C m-2). Due to the different area of herbaceous marsh, the total aboveground biomass of herbaceous marsh vegetation in different marsh distribution regions was the largest in the temperate humid and semi-humid marsh region(9.6±2.6 Tg C), and was the smallest in the coastal marsh region(1.1±0.1 Tg C). The spatial distribution of aboveground biomass of herbaceous marsh vegetation in China has obvious non-zonality characteristics, but also presents certain zonality in some regions. The aboveground biomass of herbaceous marsh vegetation in the Tibetan Plateau decreased with the increase of altitude. With the aggravation of drought, the aboveground biomass of herbaceous marsh vegetation in temperate humid and semi-humid regions and temperate arid and semi-arid regions decreased first and then did not obviously change. The aboveground biomass of herbaceous marsh vegetation in temperate humid and semi-humid regions was relatively larger in the regions with higher average annual temperature. The results can provide scientific basis for accurately evaluating the adjustment action of wetland ecosystems on climate, and provide decision support for adaptive management of wetland ecosystems.
基金supported by the National Natural Science Foundation of China under Grant Nos.61070172 and 10990011the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No. XDA06010702the State Key Laboratory of Information Security,Chinese Academy of Sciences
文摘Boolean functions used in a cryptographic system should have high algebraic immunity to resist algebraic attacks. This paper presents a matrix method for constructing balanced Boolean functions achieving maximum algebraic immunity.
基金supported by the Fundamental Research Funds for the Central Universities (Nos. FRF-TP-14025A1 and FRF-TP-15-025A2)supported by the Key Technologies Research and Development Program of 12th Five-Year Plan of China (No.2013BAI13B06)
文摘In this paper, we study the skyline group problem over a data stream. An object can dominate another object if it is not worse than the other object on all attributes and is better than the other object on at least one attribute. If an object cannot be dominated by any other object, it is a skyline object. The skyline group problem involves finding k-item groups that cannot be dominated by any other k-item group. Existing algorithms designed to find skyline groups can only process static data. However, data changes as a stream with time in many applications,and algorithms should be designed to support skyline group queries on dynamic data. In this paper, we propose new algorithms to find skyline groups over a data stream. We use data structures, namely a hash table, dominance graph, and matrix, to store dominance information and update results incrementally. We conduct experiments on synthetic datasets to evaluate the performance of the proposed algorithms. The experimental results show that our algorithms can efficiently find skyline groups over a data stream.
基金supported by the National Natural Science Foundation of China(No.11871191)the Science Foundation of Hebei Province(No.A2019106037)+1 种基金the Graduate Student Innovation Project Foundation of Hebei Province(No.CXZZBS2022066)the Key Foundation of Hebei Normal University(Nos.L2018Z01,L2021Z01)
文摘Almansi-type decomposition theorem for bi-k-regular functions defined in a star-like domainΩ⊆R^(n+1)×R^(n+1)centered at the origin with values in the Clifford algebra Cl_(2n+2,0)(R)is proved.As a corollary,Almansi-type decomposition theorem for biharmonic functions of degree k is given.
