Knowledge representation learning with entity descriptions,hierarchical types,and textual relations     

Xing Tang  Ling Chen  Jun Cui  Baogang Wei 《Information processing & management》2019,56(3):809-822

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Neural embedding-based indices for semantic search     

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   

Triggering effects of mobile video marketing in nature tourism: Media richness perspective     

Ari Alamäki  Juho Pesonen  Amir Dirin 《Information processing & management》2019,56(3):756-770

The aim of this study was to investigate videos as potential triggers of behavior. Therefore, we applied the theories of triggers and media richness to learn about the triggering efficiency of mobile marketing videos on participants’ behavioral intentions. The experiment involved three distinct test groups, each comprising 41 student participants. From the perspective of media richness theory, we observed that the different kinds of videos had quite similar effects in terms of triggering behavioral changes. However, the mechanisms explaining why triggers were present differed for each video. Further, the results reveal that the consumer's position in the information search process was the most significant reason for the triggering of any kind of effect. In addition, the instructionally designed videos were able to exert an affective triggering effect: the more participants liked the video, the more it affected their participation intention and recall scores. This study extends the media richness research by demonstrating that the effects of media richness can vary within technically similar videos, as they form different logical connections among non-verbal visual cues related to a video's storyline.  相似文献   

Advanced Arabic Natural Language Processing (ANLP) and its applications: Introduction to the special issue     

Yaser Jararweh  Mahmoud Al-Ayyoub  Elhadj Benkhelifa 《Information processing & management》2019,56(2):259-261

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Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis     

Kai Hu  Qing Luo  Kunlun Qi  Siluo Yang  Jin Mao  Xiaokang Fu  Jie Zheng  Huayi Wu  Ya Guo  Qibing Zhu 《Information processing & management》2019,56(4):1185-1203

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.  相似文献   

Writer identification approach based on bag of words with OBI features     

Amal Durou  Ibrahim Aref  Somaya Al-Maadeed  Ahmed Bouridane  Elhadj Benkhelifa 《Information processing & management》2019,56(2):354-366

Handwriter identification aims to simplify the task of forensic experts by providing them with semi-automated tools in order to enable them to narrow down the search to determine the final identification of an unknown handwritten sample. An identification algorithm aims to produce a list of predicted writers of the unknown handwritten sample ranked in terms of confidence measure metrics for use by the forensic expert will make the final decision.Most existing handwriter identification systems use either statistical or model-based approaches. To further improve the performances this paper proposes to deploy a combination of both approaches using Oriented Basic Image features and the concept of graphemes codebook. To reduce the resulting high dimensionality of the feature vector a Kernel Principal Component Analysis has been used. To gauge the effectiveness of the proposed method a performance analysis, using IAM dataset for English handwriting and ICFHR 2012 dataset for Arabic handwriting, has been carried out. The results obtained achieved an accuracy of 96% thus demonstrating its superiority when compared against similar techniques.  相似文献   

In (Big) Data we trust: Value creation in knowledge organizations - Introduction to the special issue     

Andrea De Mauro  Marco Greco  Michele Grimaldi  Paavo Ritala 《Information processing & management》2018,54(5):755-757

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我国基层统计市场主导模式建设初探     

罗放华 《湖南城市学院学报》2011,32(6):55-59

基层统计市场主导模式是由政府规范、市场主导、中介执业的基层统计生产管理模式。它是基层统计生产方式和管理方式的重大变革,对于完善我国统计管理理论,推动基层统计制度、体制机制创新具有深远的理论意义,同时对于稳固统计基础,提高宏观统计数据质量和政府统计公信力都有十分重要的现实意义。  相似文献   

出版产业化环境下编辑决策的作者意识     

周国清 《湖南城市学院学报》2011,32(5)

出版产业化环境下编辑决策要牢固树立作者意识,这是由作者及其文稿在编辑活动中的重要位置与独特作用决定的。它要求编辑主体树立与作者平等相处的理念;深入研究和准确把握作者心理;善于、敢于、巧于接受来自作者的挑战;具有善待作者的慧眼与能耐。  相似文献   

影响高等教育规模的主要因素及其协整关系——基于时间序列数据的分析   总被引：7，自引：0，他引：7  

毛建青 《北京师范大学学报(社会科学版)》2009,(2)

从1999年开始,我国高等教育规模迅速扩大,2007年高等教育毛入学率已达23%。同时,大学生就业难、文凭贬值等问题日益凸显,据此引发了人们对教育"过度"还是"不足"的争论。因此,分析我国历年来高等教育规模及其主要影响因素,并探寻它们之间的协整关系就显得非常有意义。在以往的相关研究中,学者们用最小二乘法实证分析历年高等教育规模及其影响因素之间的关系,但容易出现"伪回归"。运用动态计量经济学中的协整理论进行分析则可以解决这个问题。协整计量的结果发现,高等教育规模与四个影响因素之间确实存在稳定的长期均衡关系,其影响系数从大到小依次为总人口数、恩格尔系数、GDP发展水平和第三产业占GDP的比重。  相似文献