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排序方式: 共有4702条查询结果,搜索用时 245 毫秒
1.
Philip E. Schreur 《Cataloging & classification quarterly》2020,58(3-4):397-402
AbstractThe transformation of library metadata encoded in MARC to linked data will enable libraries to participate in the Semantic Web. This transformation, however, will be an iterative development dependent upon community-based decisions. The PCC, as a community-based organization, is ideally positioned to lead this transformation. As PCC guides this transition, three broad areas must be resolved: the conversion of legacy data to linked data, the use of identifiers to support controlled headings, and the transformation of current workflows to linked-data counterparts. By embracing the Web as a community, PCC can confirm its relevance in a complex web of global data. 相似文献
2.
Fatemeh Lashkari Ebrahim Bagheri Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755
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
3.
Molly Murphy 《Journal of Interlibrary Loan, Document Delivery & Electronic Reserve》2019,28(5):129-137
AbstractAt the University of Oklahoma, we began campus or home delivery of items from our library as well as those from other libraries. We have added more services over the years in response to requests from our users. In doing so, we found room for improvements. This paper addresses some of the issues we encountered. 相似文献
4.
《Information processing & management》2023,60(3):103280
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
5.
高稳潮 《河北职业技术学院学报》2004,4(2):31-32
信息时代的高校信息检索课应明确课程特点,构造网络同步操作环境,改革教学内容与考核方法,提高教师素质,以适应时代的要求。 相似文献
6.
通过调研分析媒体融合高速发展的2017—2019年,国内高校信息检索课程教材出版和使用情况,得出结论:信息检索课教材建设必须与时俱进,在持续发展综合性通识类教材的同时,加强专业类教材及配套教辅资料的编写,无缝对接课堂内外;契合课程教学模式更新,建设多层次立体化教材体系;对接读者需求变化,设计精准定位的场景教学内容;建立健全合作机制,联合优势力量编写精品教材。 相似文献
7.
李俊 《四川职业技术学院学报》2021,(2):44-49
公文写作是秘书学专业学生需要掌握的一项重要技能,然而,公文写作学习是一个周期长、见效慢和相对枯燥的过程,致使学生在学习过程中容易产生习得性无助心理。针对秘书学专业学生在公文写作学习中习得性无助的心理表现,通过问卷调查和访谈分析了其形成的主客观原因,并从学校工作与专业教师教学两个层面提出相应对策。 相似文献
8.
高校图书馆电子文献数据库目录网页调查分析 总被引:2,自引:0,他引:2
通过对我国87所高校图书馆电子文献教据库目录网页现状的调查,指出当前高校图书馆电子文献教据库目录网页制作中存在的问题,并提出相应的建议和措施。 相似文献
9.
文中提出了一种文本知识分析中的概念层次网络方法。该方法是一种文本概念分析的新思路。探讨了用面向对象技术与框架技术结合实现文本知识的抽象概念和具体概念的自动分析、知识组织、检索智能化方法。 相似文献
10.