在当今数字化和智能化的时代背景下,人工智能(artificial intelligence,AI)已成为科技创新的重要引擎,总结探讨AI研究的最新趋势和未来发展方向具有重要的研究和现实意义.为此,对2021—2023年间在中国计算机学会(CCF)推荐的AI领域CCF-A...在当今数字化和智能化的时代背景下,人工智能(artificial intelligence,AI)已成为科技创新的重要引擎,总结探讨AI研究的最新趋势和未来发展方向具有重要的研究和现实意义.为此,对2021—2023年间在中国计算机学会(CCF)推荐的AI领域CCF-A类国际会议和期刊所发表论文的研究成果进行收集,并在此基础上采用文献计量学的方法论来通过关键词对研究热点进行分析,进行基于高频关键词分析研究热点、基于新增关键词分析研究趋势、基于引用量加权的关键词分析高影响力研究,可以梳理AI研究的主流方向、发现AI主要研究方向的相互联系和交叉融合的特点.此外,对当前研究热点如大语言模型(large language model,LLM)、AI驱动的科学研究(AI for Science)和视觉生成相关论文的关联热点进行分析,可以挖掘技术路径和方法论的演变,展现技术创新背后的科学理论和应用前景,从而进一步揭示AI研究的最新趋势和发展前景.展开更多
Keyword search is an alternative for structured languages in querying graph-structured data.A result to a keyword query is a connected structure covering all or part of the queried keywords.The textual coverage and st...Keyword search is an alternative for structured languages in querying graph-structured data.A result to a keyword query is a connected structure covering all or part of the queried keywords.The textual coverage and structural compactness have been known as the two main properties of a relevant result to a keyword query.Many previous works examined these properties after retrieving all of the candidate results using a ranking function in a comparative manner.However,this needs a time-consuming search process,which is not appropriate for an interactive system in which the user expects results in the least possible time.This problem has been addressed in recent works by confining the shape of results to examine their coverage and compactness during the search.However,these methods still suffer from the existence of redundant nodes in the retrieved results.In this paper,we introduce the semantic of minimal covered r-clique(MCCr)for the results of a keyword query as an extended model of existing definitions.We propose some efficient algorithms to detect the MCCrs of a given query.These algorithms can retrieve a comprehensive set of non-duplicate MCCrs in response to a keyword query.In addition,these algorithms can be executed in a distributive manner,which makes them outstanding in the field of keyword search.We also propose the approximate versions of these algorithms to retrieve the top-k approximate MCCrs in a polynomial delay.It is proved that the approximate algorithms can retrieve results in two-approximation.Extensive experiments on two real-world datasets confirm the efficiency and effectiveness of the proposed algorithms.展开更多
文摘在当今数字化和智能化的时代背景下,人工智能(artificial intelligence,AI)已成为科技创新的重要引擎,总结探讨AI研究的最新趋势和未来发展方向具有重要的研究和现实意义.为此,对2021—2023年间在中国计算机学会(CCF)推荐的AI领域CCF-A类国际会议和期刊所发表论文的研究成果进行收集,并在此基础上采用文献计量学的方法论来通过关键词对研究热点进行分析,进行基于高频关键词分析研究热点、基于新增关键词分析研究趋势、基于引用量加权的关键词分析高影响力研究,可以梳理AI研究的主流方向、发现AI主要研究方向的相互联系和交叉融合的特点.此外,对当前研究热点如大语言模型(large language model,LLM)、AI驱动的科学研究(AI for Science)和视觉生成相关论文的关联热点进行分析,可以挖掘技术路径和方法论的演变,展现技术创新背后的科学理论和应用前景,从而进一步揭示AI研究的最新趋势和发展前景.
文摘Keyword search is an alternative for structured languages in querying graph-structured data.A result to a keyword query is a connected structure covering all or part of the queried keywords.The textual coverage and structural compactness have been known as the two main properties of a relevant result to a keyword query.Many previous works examined these properties after retrieving all of the candidate results using a ranking function in a comparative manner.However,this needs a time-consuming search process,which is not appropriate for an interactive system in which the user expects results in the least possible time.This problem has been addressed in recent works by confining the shape of results to examine their coverage and compactness during the search.However,these methods still suffer from the existence of redundant nodes in the retrieved results.In this paper,we introduce the semantic of minimal covered r-clique(MCCr)for the results of a keyword query as an extended model of existing definitions.We propose some efficient algorithms to detect the MCCrs of a given query.These algorithms can retrieve a comprehensive set of non-duplicate MCCrs in response to a keyword query.In addition,these algorithms can be executed in a distributive manner,which makes them outstanding in the field of keyword search.We also propose the approximate versions of these algorithms to retrieve the top-k approximate MCCrs in a polynomial delay.It is proved that the approximate algorithms can retrieve results in two-approximation.Extensive experiments on two real-world datasets confirm the efficiency and effectiveness of the proposed algorithms.
