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1.
Image and text matching bridges visual and textual modality differences and plays a considerable role in cross-modal retrieval. Much progress has been achieved through semantic representation and alignment. However, the distribution of multimedia data is severely unbalanced and contains many low-frequency occurrences, which are often ignored and cause performance degradation, i.e., the long-tail effect. In this work, we propose a novel rare-aware attention network (RAAN), which explores and exploits textual rare content for tackling the long-tail effect of image and text matching. Specifically, we first design a rare-aware mining module, which contains global prior information construction and rare fragment detector for modeling the characteristic of rare content. Then, the rare attention matching utilizes prior information as attention to guide the representation enhancement of rare content and introduces the rareness representation to strengthen the similarity calculation. Finally, we design prior information loss to optimize the model together with the triplet loss. We perform quantitative and qualitative experiments on two large-scale databases and achieve leading performance. In particular, we conduct 0-shot test for rare content and improve rSum by 21.0 and 41.5 on Flickr30K (155,000 image and text pairs) and MSCOCO (616,435 image and text pairs), demonstrating the effectiveness of the proposed method for the long-tail effect.  相似文献   
2.
[目的/意义]社交媒体是网络信息资源的重要组成部分,对国内外社交媒体存档的相关研究成果进行总结与梳理,形成比较完整的综述内容,为国内该领域研究提供参考与借鉴。[方法/过程]基于多学科视角,通过文献计量与内容分析得到社交媒体存档领域的文献分布情况,总结社交媒体存档的理论基础,从宏观层面将社交媒体存档理论与实践研究归纳为"目的与主体""政策与指南""问题与障碍"三个研究主题并展开综述。[结果/结论]国内外社交媒体存档研究具有发展速度较快、与实践结合紧密、区域发展不均衡等特征,在未来研究中需要重视研究对象的变化、管理标准的构建以及多主体间的协作。最后对国内社交媒体存档研究与实践的发展提出建议。  相似文献   
3.
Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus.  相似文献   
4.
Semantic knowledge accumulates through explicit means and productive processes (e.g., analogy). These means work in concert when information explicitly acquired in separate episodes is integrated, and the integrated representation is used to self-derive new knowledge. We tested whether (a) self-derivation through memory integration extends beyond general information to science content, (b) self-derived information is retained, and (c) details of explicit learning episodes are retained. Testing was in second-grade classrooms (children 7–9 years). Children self-derived new knowledge; performance did not differ for general knowledge (Experiment 1) and science curriculum facts (Experiment 2). In Experiment 1, children retained self-derived knowledge over one week. In Experiment 2, children remembered details of the learning episodes that gave rise to self-derived knowledge; performance suggests that memory integration is dependent on explicit prompts. The findings support nomination of self-derivation through memory integration as a model for accumulation of semantic knowledge and inform the processes involved.  相似文献   
5.
为深入理解图书情报学学术论文中所使用的研究方法的语义功能,为用户提供基于知识单元的细粒度知识服务,文章首先基于体裁理论来分析引文分析法、田野研究法、共词分析法、实验法、比较分析法和问卷调查法的知识单元构成。其次采用文本分析法,检索CSSCI图书情报学领域的18种期刊中使用以上6种研究方法的论文,进行知识单元层次的深度标引,作为知识库构建的语料。再次采用系统设计法,开发具有4种功能的学术论文研究方法学习系统。最后采用实验法,招募30位研究生使用系统,并根据用户体验对其可用性进行评价。结果表明:研究方法的体裁分析能较好地表示使用该方法开展研究的论文的语义功能,解释研究方法使用过程各部分的语义特征,为深入到知识单元层面的标引提供了基础,也为用户提供了基于知识单元的细粒度的检索点,知识库具有很好的可用性。文章揭示了论文研究方法使用过程各部分的语义特征,基于知识单元构成而设计的学术论文研究方法知识库能有效帮助用户学习研究方法,为学术论文研究方法内容的深度语义标引和本体开发奠定了基础,也为用户提供细粒度、多维度的论文研究方法内容的检索服务,对面向知识发现的知识组织研究具有参考意义。  相似文献   
6.
本文以虚拟现实技术、虚拟设计以及网络应用技术等理论为基础,深入研究了基于Web虚拟设计系统的实现方法。以虚拟现实技术为平台,整合多种网络技术,用软件实现虚拟现实的方法,构建了一个以B/S为体系结构的虚拟设计系统实例。  相似文献   
7.
基于威客网的知识市场研究   总被引:1,自引:0,他引:1  
威客网成功实现了知识的网上交易,为建立完善的知识市场提供了一些参考和借鉴。在威客网的基础上,对于威客网的知识市场模型进行了分析,并提出了构建基于威客网的知识市场的基本框架。  相似文献   
8.
网络环境下复合图书馆知识组织探讨   总被引:4,自引:0,他引:4  
孙玉英  高在元 《情报科学》2006,24(12):1870-1873
发展是硬道理,复合图书馆是未来发展模式,知识组织是其核心建设,复合图书馆知识组织工具对传统文献和数字资源进行整合挖掘,建立知识导航和知识语义网。  相似文献   
9.
The performance and capabilities of Web search engines is an important and significant area of research. Millions of people world wide use Web search engines very day. This paper reports the results of a major study examining the overlap among results retrieved by multiple Web search engines for a large set of more than 10,000 queries. Previous smaller studies have discussed a lack of overlap in results returned by Web search engines for the same queries. The goal of the current study was to conduct a large-scale study to measure the overlap of search results on the first result page (both non-sponsored and sponsored) across the four most popular Web search engines, at specific points in time using a large number of queries. The Web search engines included in the study were MSN Search, Google, Yahoo! and Ask Jeeves. Our study then compares these results with the first page results retrieved for the same queries by the metasearch engine Dogpile.com. Two sets of randomly selected user-entered queries, one set was 10,316 queries and the other 12,570 queries, from Infospace’s Dogpile.com search engine (the first set was from Dogpile, the second was from across the Infospace Network of search properties were submitted to the four single Web search engines). Findings show that the percent of total results unique to only one of the four Web search engines was 84.9%, shared by two of the three Web search engines was 11.4%, shared by three of the Web search engines was 2.6%, and shared by all four Web search engines was 1.1%. This small degree of overlap shows the significant difference in the way major Web search engines retrieve and rank results in response to given queries. Results point to the value of metasearch engines in Web retrieval to overcome the biases of individual search engines.  相似文献   
10.
随着企业在发展过程中环境保护和可持续发展的意识不断加深,绿色供应链的发展和应用成为学者们的研究热点。本文将从Web of Science和CNKI中以“绿色供应链”为主题检索到的1521篇文献作为研究对象,利用文献分析工具HistCite和CiteSpace,分别从发文的时间、作者、机构、国家/地区以及热点文献等方面进行可视化分析,以期能够对绿色供应链领域的研究现状有一个全方位的了解和把握,并在最后展望了我国未来在该领域的研究方向。  相似文献   
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